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Altay C, Başara Akın I, Özgül HA, Şen V, Bozkurt O, Tuna EB, Yörükoğlu K, Seçil M. Is fat quantification based on proton density fat fraction useful for differentiating renal tumor types? Abdom Radiol (NY) 2025; 50:1254-1265. [PMID: 39333411 DOI: 10.1007/s00261-024-04596-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2024] [Revised: 09/12/2024] [Accepted: 09/16/2024] [Indexed: 09/29/2024]
Abstract
PURPOSE This study retrospectively assessed the diagnostic accuracy of fat quantification based on proton density fat fraction (PDFF) for differentiating renal tumors. METHODS In this retrospective study, 98 histologically confirmed clear cell renal cell carcinomas (ccRCCs), 35 papillary renal cell carcinomas (pRCCs), 14 renal oncocytomas, 16 chromophobe renal cell carcinomas (chRCCs), 10 lymphomas, 19 uroepithelial tumors, 10 lipid-poor angiomyolipomas (AMLs), and 25 lipid-rich AMLs were identified in 226 patients (127 males and 99 females) over 5 years. All patients underwent multiparametric kidney MRI. The MRI protocol included an axial plane and a volumetric 3D fat fraction sequence known as mDIXON-Quant for PDFF measurement. Demographic data were recorded, and PDFF values were independently reviewed by two radiologists blinded to pathologic results. MRI examinations were performed using a 1.5 T system. MRI-PDFF measurements were obtained from the solid parts of all renal tumors. Fat quantification was performed using a standard region of interest for each tumor, compared to histopathological diagnoses. Sensitivity and specificity analyses were performed to calculate the diagnostic accuracy for each histopathological tumor type. Nonparametric variables were compared among the subgroups using the Kruskal-Wallis H test and Mann Whitney U test. P-values < 0.05 were considered statistically significant. RESULTS In all, 102 patients underwent partial nephrectomy, 70 patients underwent radical nephrectomy, and the remaining 54 had biopsies. Patient age (mean: 58.11 years; range: 18-87 years) and tumor size (mean: 29.5 mm; range: 14-147 mm) did not significantly differ across groups. All measurements exhibited good interobserver agreement. The mean ccRCC MRI-PDFF was 12.6 ± 5.06% (range: 11.58-13.61%), the mean pRCC MRI-PDFF was 2.72 ± 2.42% (range: 2.12-3.32%), and the mean chRCC MRI-PDFF was 1.8 ± 1.4% (range: 1.09-2.5%). Clear cell RCCs presented a significantly higher fat ratio than other RCC types, uroepithelial tumors, lymphomas, and lipid-poor AMLs (p < 0.05). Lipid-rich AMLs demonstrated a very high fat ratio. CONCLUSION MRI-PDFF facilitated accurate differentiation of ccRCCs from other renal tumors with high sensitivity and specificity.
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Qi H, Jiang S, Nan J, Guo H, Cheng C, He X, Jin H, Zhang R, Lei J. Application and research progress of magnetic resonance proton density fat fraction in metabolic dysfunction-associated steatotic liver disease: a comprehensive review. Abdom Radiol (NY) 2025; 50:185-197. [PMID: 39048719 DOI: 10.1007/s00261-024-04448-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Revised: 06/06/2024] [Accepted: 06/07/2024] [Indexed: 07/27/2024]
Abstract
Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD), formerly known as Non-Alcoholic Fatty Liver Disease (NAFLD), is a chronic liver disorder associated with disturbances in lipid metabolism. The disease is prevalent worldwide, particularly closely linked with metabolic syndromes such as obesity and diabetes. Magnetic Resonance Proton Density Fat Fraction (MRI-PDFF), serving as a non-invasive and highly quantitative imaging assessment tool, holds promising applications in the diagnosis and research of MASLD. This paper aims to comprehensively review and summarize the applications and research progress of MRI-PDFF technology in MASLD, analyze its strengths and challenges, and anticipate its future developments in clinical practice.
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Affiliation(s)
- Hongyan Qi
- The First Clinical Medical College of Lanzhou University, No.1 Donggang West Road, Chengguan District, Lanzhou City, 730000, Gansu Province, China
| | | | - Jiang Nan
- Department of Radiology, The First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Hang Guo
- Department of Radiology, The First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Cai Cheng
- Department of Radiology, The First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Xin He
- Department of Radiology, The First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Hongyang Jin
- Department of Radiology, The First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Rongfan Zhang
- Department of Radiology, The First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Junqiang Lei
- The First Clinical Medical College of Lanzhou University, No.1 Donggang West Road, Chengguan District, Lanzhou City, 730000, Gansu Province, China.
- Department of Radiology, The First Hospital of Lanzhou University, Lanzhou, Gansu, China.
- Radiological Clinical Medicine Research Center of Gansu Province, Lanzhou, Gansu, China.
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Yuan K, Liu Q, Luo P, Wang C, Zhou Y, Qi F, Zhang Q, Huang X, Qiu B. Association of proton-density fat fraction with osteoporosis: a systematic review and meta-analysis. Osteoporos Int 2024; 35:2077-2086. [PMID: 39129009 DOI: 10.1007/s00198-024-07220-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 07/29/2024] [Indexed: 08/13/2024]
Abstract
This study aimed to evaluate the correlation between measuring proton-density fat fraction (PDFF) in bone marrow using multi-echo chemical shift-encoded MRI and osteoporosis, assessing its effectiveness as a biomarker for osteoporosis. A systematic review was conducted by two independent researchers using Cochrane, PubMed, EMBASE, and Web of Science databases up to December 2023. Quality assessments were evaluated using the Cochrane risk of bias tool and the Agency for Healthcare Research and Quality (AHRQ) checklist. Fourteen studies involving 1495 patients were analyzed. The meta-analysis revealed a significant difference in PDFF values between the osteoporosis/osteopenia group and the normal control group, with a mean difference of 11.04 (95% CI: 9.17 to 12.92, Z=11.52, P < 0.00001). Measuring PDFF via MRI shows potential as an osteoporosis biomarker and may serve as a risk factor for osteoporosis. This insight opens new avenues for future diagnostic and therapeutic strategies, potentially improving osteoporosis management and patient care. OBJECTIVE This study aims to assess the correlation between measuring proton-density fat fraction (PDFF) in bone marrow using multi-echo chemical shift-encoded MRI and osteoporosis, evaluating its effectiveness as a biomarker for osteoporosis. MATERIALS AND METHODS This systematic review was carried out by two independent researchers using Cochrane, PubMed, EMBASE, and Web of Science databases up to December 2023. Quality assessments were evaluated using the Cochrane risk of bias tool and the Agency for Healthcare Research and Quality (AHRQ) checklist. RESULTS Fourteen studies involving 1495 patients were analyzed. The meta-analysis revealed a significant difference in PDFF values between the osteoporosis/osteopenia group and the normal control group, with a (MD = 11.04, 95% CI: 9.17 to 12.92, Z = 11.52, P < 0.00001). Subgroup analyses indicated that diagnostic methods, gender, and echo length did not significantly impact the PDFF-osteoporosis association. CONCLUSION PDFF measurement via MRI shows potential as an osteoporosis biomarker and may serve as a risk factor for osteoporosis. This insight opens new avenues for future diagnostic and therapeutic strategies, potentially improving osteoporosis management and patient care.
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Affiliation(s)
- Kecheng Yuan
- Medical Imaging Center, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China
| | - Qingyun Liu
- Medical Imaging Center, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China
| | - Penghui Luo
- Medical Imaging Center, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China
| | - Changliang Wang
- Medical Imaging Center, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China
| | - Yufu Zhou
- Anhui Fuqing Medical Equipment Co., Ltd., Hefei, China
| | - Fulang Qi
- Medical Imaging Center, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China
| | - Qing Zhang
- Medical Imaging Center, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China
| | - Xiaoyan Huang
- Anhui Fuqing Medical Equipment Co., Ltd., Hefei, China
| | - Bensheng Qiu
- Medical Imaging Center, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China.
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Ma M, Cheng J, Li X, Fan Z, Wang C, Reeder SB, Hernando D. Prediction of MRI R 2 * $$ {\mathrm{R}}_2^{\ast } $$ relaxometry in the presence of hepatic steatosis by Monte Carlo simulations. NMR IN BIOMEDICINE 2024:e5274. [PMID: 39394902 DOI: 10.1002/nbm.5274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 09/14/2024] [Accepted: 09/30/2024] [Indexed: 10/14/2024]
Abstract
To develop Monte Carlo simulations to predict the relationship ofR 2 * $$ {\mathrm{R}}_2^{\ast } $$ with liver fat content at 1.5 T and 3.0 T. For various fat fractions (FFs) from 1% to 25%, four types of virtual liver models were developed by incorporating the size and spatial distribution of fat droplets. Magnetic fields were then generated under different fat susceptibilities at 1.5 T and 3.0 T, and proton movement was simulated for phase accrual and MRI signal synthesis. The synthesized signal was fit to single-peak and multi-peak fat signal models forR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and proton density fat fraction (PDFF) predictions. In addition, the relationships betweenR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and PDFF predictions were compared with in vivo calibrations and Bland-Altman analysis was performed to quantitatively evaluate the effects of these components (type of virtual liver model, fat susceptibility, and fat signal model) onR 2 * $$ {\mathrm{R}}_2^{\ast } $$ predictions. A virtual liver model with realistic morphology of fat droplets was demonstrated, andR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and PDFF values were predicted by Monte Carlo simulations at 1.5 T and 3.0 T.R 2 * $$ {\mathrm{R}}_2^{\ast } $$ predictions were linearly correlated with PDFF, while the slope was unaffected by the type of virtual liver model and increased as fat susceptibility increased. Compared with in vivo calibrations, the multi-peak fat signal model showed superior performance to the single-peak fat signal model, which yielded an underestimation of liver fat. TheR 2 * $$ {\mathrm{R}}_2^{\ast } $$ -PDFF relationships by simulations with fat susceptibility of 0.6 ppm and the multi-peak fat signal model wereR 2 * = 0.490 × PDFF + 28.0 $$ {\mathrm{R}}_2^{\ast }=0.490\times \mathrm{PDFF}+28.0 $$ (R 2 = 0.967 $$ {R}^2=0.967 $$ ,p < 0.01 $$ p<0.01 $$ ) at 1.5 T andR 2 * = 0.928 × PDFF + 39.4 $$ {\mathrm{R}}_2^{\ast }=0.928\times \mathrm{PDFF}+39.4 $$ (R 2 = 0.972 $$ {R}^2=0.972 $$ ,p < 0.01 $$ p<0.01 $$ ) at 3.0 T. Monte Carlo simulations provide a new means forR 2 * $$ {\mathrm{R}}_2^{\ast } $$ -PDFF prediction, which is primarily determined by fat susceptibility, fat signal model, and magnetic field strength. AccurateR 2 * $$ {\mathrm{R}}_2^{\ast } $$ -PDFF calibration has the potential to correct the effect of fat onR 2 * $$ {\mathrm{R}}_2^{\ast } $$ quantification, and may be helpful for accurateR 2 * $$ {\mathrm{R}}_2^{\ast } $$ measurements in liver iron overload. In this study, a Monte Carlo simulation of hepatic steatosis was developed to predict the relationship betweenR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and PDFF. Furthermore, the effects of fat droplet morphology, fat susceptibility, fat signal model, and magnetic field strength were evaluated for theR 2 * $$ {\mathrm{R}}_2^{\ast } $$ -PDFF calibration. Our results suggest that Monte Carlo simulations provide a new means forR 2 * $$ {\mathrm{R}}_2^{\ast } $$ -PDFF prediction and this means can be easily generated for various regimes, such as simulations with higher fields and different echo times, as well as correction of magnetic susceptibility measurements for liver iron quantification.
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Affiliation(s)
- Mengyuan Ma
- School of Biomedical Engineering, Anhui Medical University, Hefei, China
| | - Junying Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xiaoben Li
- School of Biomedical Engineering, Anhui Medical University, Hefei, China
| | - Zhuangzhuang Fan
- School of Biomedical Engineering, Anhui Medical University, Hefei, China
| | - Changqing Wang
- School of Biomedical Engineering, Anhui Medical University, Hefei, China
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Scott B Reeder
- Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin, Madison, Wisconsin, USA
- Department of Biomedical Engineering, University of Wisconsin, Madison, Wisconsin, USA
- Department of Medicine, University of Wisconsin, Madison, Wisconsin, USA
- Department of Emergency Medicine, University of Wisconsin, Madison, Wisconsin, USA
| | - Diego Hernando
- Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin, Madison, Wisconsin, USA
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Stuhlfaut J. Editorial Comment: Quantitative Ultrasound 101-A Guide to Emerging Techniques in the Noninvasive Diagnosis and Staging of Liver Disease. AJR Am J Roentgenol 2024. [PMID: 39356489 DOI: 10.2214/ajr.24.32078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/03/2024]
Affiliation(s)
- Joshua Stuhlfaut
- President, South Shore Radiological Associates Staff Radiologist, South Shore Hospital, Weymouth, MA
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Liu J, Wu Y, Tian C, Zhang X, Su Z, Nie L, Wang R, Zeng X. Quantitative assessment of renal steatosis in patients with type 2 diabetes mellitus using the iterative decomposition of water and fat with echo asymmetry and least squares estimation quantification sequence imaging: repeatability and clinical implications. Quant Imaging Med Surg 2024; 14:7341-7352. [PMID: 39429570 PMCID: PMC11485345 DOI: 10.21037/qims-24-330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Accepted: 08/14/2024] [Indexed: 10/22/2024]
Abstract
Background Fatty kidney disease is linked to renal function damage, but there is no noninvasive tool for monitoring renal fat accumulation. This study aimed to explore the repeatability of the iterative decomposition of water and fat with echo asymmetry and least squares estimation quantification (IDEAL-IQ) sequence imaging in quantifying renal fat deposition and to assess the differences observed in patients with type 2 diabetes mellitus (T2DM). Methods A total of 26 healthy participants underwent two IDEAL-IQ scans without repositioning, and the repeatability of the imaging technique was assessed with Bland-Altman analysis. Additionally, 96 patients with T2DM underwent a single IDEAL-IQ scan for the examination of renal fat deposition. The patients with T2DM were classified into three groups based on their estimated glomerular filtration rate (eGFR). One-way analysis of variance was used to analyze the differences of renal fat depositions between the groups. Receiver operating characteristic curve analysis was used to assess the diagnostic performance of IDEAL-IQ. Results Bland-Altman analyses showed narrower limits of agreement and a significant correlation (r=0.81; P<0.05) between the two IDEAL-IQ scans. Statistically significant differences between the healthy volunteers and patients with T2DM, diabetic kidney disease (DKD) I-II, and or DKD III-IV were found in renal parenchymal proton-density fat fraction (PDFF) values (P<0.001). Renal parenchymal PDFF was negatively correlated with eGFR (r=-0.437; P<0.001) and positive correlated with serum creatinine level (µmol/L) (r=0.421; P<0.001). The area under the curve of IDEAL-IQ in discriminating between the healthy volunteers and patients with T2DM was 0.857. For discriminating T2DM from DKD I-II and DKD III-IV, the IDEAL-IQ had an area under the curve of 0.689 and 0.823, respectively. Conclusions IDEAL-IQ is a promising and reproducible technique for the assessment of renal fat deposition and identification of risk of DKD in patients with T2DM. Moreover, IDEAL-IQ imaging is expected to improve the sensitivity and specificity of early renal function damage and staging assessment of patients with T2DM.
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Affiliation(s)
- Jian Liu
- Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province, State Key Laboratory of Public Big Data, College of Computer Science and Technology, Guizhou University, Guiyang, China
- Department of Radiology, International Exemplary Cooperation Base of Precision Imaging for Diagnosis and Treatment, Guizhou Provincial People’s Hospital, Guiyang, China
| | - Yu Wu
- Department of Radiology, International Exemplary Cooperation Base of Precision Imaging for Diagnosis and Treatment, Guizhou Provincial People’s Hospital, Guiyang, China
- Department of Graduate School, Zunyi Medical University, Zunyi, China
| | - Chong Tian
- Department of Radiology, International Exemplary Cooperation Base of Precision Imaging for Diagnosis and Treatment, Guizhou Provincial People’s Hospital, Guiyang, China
| | - Xunlan Zhang
- Department of Graduate School, Zunyi Medical University, Zunyi, China
| | - Zhijie Su
- Department of Graduate School, Zunyi Medical University, Zunyi, China
| | - Lisha Nie
- GE HealthCare Magnetic Resonance Research, Beijing, China
| | - Rongpin Wang
- Department of Radiology, International Exemplary Cooperation Base of Precision Imaging for Diagnosis and Treatment, Guizhou Provincial People’s Hospital, Guiyang, China
| | - Xianchun Zeng
- Department of Radiology, International Exemplary Cooperation Base of Precision Imaging for Diagnosis and Treatment, Guizhou Provincial People’s Hospital, Guiyang, China
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Jonuscheit M, Uhlemeyer C, Korzekwa B, Schouwink M, Öner-Sieben S, Ensenauer R, Roden M, Belgardt BF, Schrauwen-Hinderling VB. Post mortem analysis of hepatic volume and lipid content by magnetic resonance imaging and spectroscopy in fixed murine neonates. NMR IN BIOMEDICINE 2024; 37:e5140. [PMID: 38556731 DOI: 10.1002/nbm.5140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 01/31/2024] [Accepted: 02/14/2024] [Indexed: 04/02/2024]
Abstract
Maternal obesity and hyperglycemia are linked to an elevated risk for obesity, diabetes, and steatotic liver disease in the adult offspring. To establish and validate a noninvasive workflow for perinatal metabolic phenotyping, fixed neonates of common mouse strains were analyzed postmortem via magnetic resonance imaging (MRI)/magnetic resonance spectroscopy (MRS) to assess liver volume and hepatic lipid (HL) content. The key advantage of nondestructive MRI/MRS analysis is the possibility of further tissue analyses, such as immunohistochemistry, RNA extraction, and even proteomics, maximizing the data that can be gained per individual and therefore facilitating comprehensive correlation analyses. This study employed an MRI and 1H-MRS workflow to measure liver volume and HL content in 65 paraformaldehyde-fixed murine neonates at 11.7 T. Liver volume was obtained using semiautomatic segmentation of MRI acquired by a RARE sequence with 0.5-mm slice thickness. HL content was measured by a STEAM sequence, applied with and without water suppression. T1 and T2 relaxation times of lipids and water were measured for respective correction of signal intensity. The HL content, given as CH2/(CH2 + H2O), was calculated, and the intrasession repeatability of the method was tested. The established workflow yielded robust results with a variation of ~3% in repeated measurements for HL content determination. HL content measurements were further validated by correlation analysis with biochemically assessed triglyceride contents (R2 = 0.795) that were measured in littermates. In addition, image quality also allowed quantification of subcutaneous adipose tissue and stomach diameter. The highest HL content was measured in C57Bl/6N (4.2%) and the largest liver volume and stomach diameter in CBA (53.1 mm3 and 6.73 mm) and NMRI (51.4 mm3 and 5.96 mm) neonates, which also had the most subcutaneous adipose tissue. The observed effects were independent of sex and litter size. In conclusion, we have successfully tested and validated a robust MRI/MRS workflow that allows assessment of morphology and HL content and further enables paraformaldehyde-fixed tissue-compatible subsequent analyses in murine neonates.
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Affiliation(s)
- Marc Jonuscheit
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Institute for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- German Center for Diabetes Research (DZD e.V.), München-Neuherberg, Germany
| | - Celina Uhlemeyer
- German Center for Diabetes Research (DZD e.V.), München-Neuherberg, Germany
- Institute for Vascular and Islet Cell Biology, German Diabetes Center, Leibniz Institute for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Benedict Korzekwa
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Institute for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- German Center for Diabetes Research (DZD e.V.), München-Neuherberg, Germany
| | - Marten Schouwink
- University Children's Hospital, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Soner Öner-Sieben
- Institute of Child Nutrition, Max Rubner-Institut, Federal Research Institute of Nutrition and Food, Karlsruhe, Germany
| | - Regina Ensenauer
- Institute of Child Nutrition, Max Rubner-Institut, Federal Research Institute of Nutrition and Food, Karlsruhe, Germany
| | - Michael Roden
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Institute for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- German Center for Diabetes Research (DZD e.V.), München-Neuherberg, Germany
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Bengt-Frederik Belgardt
- German Center for Diabetes Research (DZD e.V.), München-Neuherberg, Germany
- Institute for Vascular and Islet Cell Biology, German Diabetes Center, Leibniz Institute for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Vera B Schrauwen-Hinderling
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Institute for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- German Center for Diabetes Research (DZD e.V.), München-Neuherberg, Germany
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
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Horn F, Ittermann T, Kromrey ML, Seppelt D, Völzke H, Kühn JP, Schön F. Exploring factors associated with non-alcoholic fatty liver disease using longitudinal MRI. BMC Gastroenterol 2024; 24:229. [PMID: 39044153 PMCID: PMC11267668 DOI: 10.1186/s12876-024-03300-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2023] [Accepted: 06/19/2024] [Indexed: 07/25/2024] Open
Abstract
BACKGROUND To identify factors associated with non-alcoholic fatty liver disease over a 5-year period. METHODS Three hundred seven participants, including 165 women, with a mean age of 55.6 ± 12.0 years underwent continuous quantitative MRI of the liver using the proton-density fat fraction (PDFF). The liver's fat fractions were determined at baseline and 5 years later, and the frequency of participants who developed fatty liver disease and potential influencing factors were explored. Based on significant factors, a model was generated to predict the development of fatty liver disease. RESULTS After excluding participants with pre-existing fatty liver, the baseline PDFF of 3.1 ± 0.9% (n = 190) significantly increased to 7.67 ± 3.39% within 5 years (p < 0.001). At baseline, age (OR = 1.04, p = 0.006, CI = 1.01-1.07), BMI (OR = 1.11, p = 0.041, CI = 1.01-1.23), and waist circumference (OR = 1.05, p = 0.020, CI = 1.01-1.09) were identified as risk factors. Physical activity was negatively associated (OR = 0.43, p = 0.049, CI = 0.18-0.99). In the prediction model, age, physical activity, diabetes mellitus, diastolic blood pressure, and HDL-cholesterol remained as independent variables. Combining these risk factors to predict the development of fatty liver disease revealed an AUC of 0.7434. CONCLUSIONS Within a five-year follow-up, one-quarter of participants developed fatty liver disease influenced by the triggering factors of age, diabetes mellitus, low HDL-cholesterol, and diastolic blood pressure. Increased physical activity has a protective effect on the development of fatty liver.
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Affiliation(s)
- Friedrich Horn
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Till Ittermann
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Marie-Luise Kromrey
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
- Institute and Policlinic for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Danilo Seppelt
- Institute and Policlinic for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Jens-Peter Kühn
- Institute and Policlinic for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.
| | - Felix Schön
- Institute and Policlinic for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
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Kubale R, Schneider G, Lessenich CPN, Buecker A, Wassenberg S, Torres G, Gurung A, Hall T, Labyed Y. Ultrasound-Derived Fat Fraction for Hepatic Steatosis Assessment: Prospective Study of Agreement With MRI PDFF and Sources of Variability in a Heterogeneous Population. AJR Am J Roentgenol 2024; 222:e2330775. [PMID: 38506537 DOI: 10.2214/ajr.23.30775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/21/2024]
Abstract
BACKGROUND. Metabolic dysfunction-associated steatotic liver disease is a growing global public health concern. Quantitative ultrasound measurements, such as ultrasound-derived fat fraction (UDFF), could provide noninvasive, cost-effective, and portable steatosis evaluation. OBJECTIVE. The purpose of this article was to evaluate utility of UDFF for steatosis assessment using proton density fat fraction (PDFF) as reference in patients undergoing liver MRI for heterogeneous indications and to assess UDFF variability. METHODS. This prospective study included a primary analysis of 187 patients (mean age, 53.8 years; 112 men, 75 women) who underwent 3-T liver MRI for any clinical indication from December 2020 to July 2021. Patients underwent investigational PDFF measurement, including determination of PDFFwhole-liver (mean PDFF of entire liver), and PDFFvoxel (PDFF in single voxel within right lobe, measured by MR spectroscopy), as well as investigational ultrasound with UDFF calculation (mean of five inter-costal measurements) within 1 hour after MRI. In a subanalysis, 21 of these patients underwent additional UDFF measurements 1, 3, and 5 hours after meal consumption. The study also included repeatability and reproducibility analysis of 30 patients (mean age, 26.3 years; 10 men, 20 women) who underwent clinical abdominal ultrasound between November 2022 and January 2023; in these patients, three operators sequentially performed UDFF measurements. RESULTS. In primary analysis, UDFF and PDFFwhole-liver measurements showed intra-class correlation coefficient (ICC) of 0.79. In Bland-Altman analysis, UDFF and PDFFvoxel measurements showed mean difference of 1.5% (95% CI, 0.6-2.4%), with 95% limits of agreement from -11.0% to 14.0%. UDFF measurements exhibited AUC for detecting PDFFvoxel at historic thresholds of 6.5% and greater, 17.4% and greater, and 22.1% and greater of 0.90, 0.95, and 0.95, respectively. In subanalysis, mean UDFF was not significantly different across time points with respect to meal consumption (p = .21). In repeatability and reproducibility analysis, ICC for intraoperator repeatability ranged from 0.98 to 0.99 and for interoperator reproducibility from 0.90 to 0.96. Visual assessment of patient-level data plots indicated increasing variability of mean UDFF measurements across operators and of intercostal measurements within individual patients with increasing steatosis. CONCLUSION. UDFF showed robust agreement with PDFF, diagnostic performance for steatosis grades, and intraoperator repeatability and interoperator reproducibility. Nonetheless, UDFF exhibited bias toward slightly larger values versus PDFF; intraoperator and interoperator variation increased with increasing steatosis. CLINICAL IMPACT. UDFF shows promise for steatosis assessment across diverse populations, although continued optimization remains warranted.
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Affiliation(s)
- Reinhard Kubale
- Clinic of Diagnostic and Interventional Radiology, Saarland University Hospital, Kirrberger Strasse Geb. 50.1, 66424 Homburg, Germany
| | - Guenther Schneider
- Clinic of Diagnostic and Interventional Radiology, Saarland University Hospital, Kirrberger Strasse Geb. 50.1, 66424 Homburg, Germany
| | - Carl P N Lessenich
- Clinic of Diagnostic and Interventional Radiology, Saarland University Hospital, Kirrberger Strasse Geb. 50.1, 66424 Homburg, Germany
| | - Arno Buecker
- Clinic of Diagnostic and Interventional Radiology, Saarland University Hospital, Kirrberger Strasse Geb. 50.1, 66424 Homburg, Germany
| | | | | | - Arati Gurung
- Siemens Healthineers Ultrasound Division, Issaquah, WA
| | - Timothy Hall
- Department of Medical Physics, University of Wisconsin, Madison, WI
| | - Yassin Labyed
- Siemens Healthineers Ultrasound Division, Issaquah, WA
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10
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Li S, Wang Z, Ding Z, She H, Du YP. Accelerated four-dimensional free-breathing whole-liver water-fat magnetic resonance imaging with deep dictionary learning and chemical shift modeling. Quant Imaging Med Surg 2024; 14:2884-2903. [PMID: 38617145 PMCID: PMC11007520 DOI: 10.21037/qims-23-1396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Accepted: 02/13/2024] [Indexed: 04/16/2024]
Abstract
Background Multi-echo chemical-shift-encoded magnetic resonance imaging (MRI) has been widely used for fat quantification and fat suppression in clinical liver examinations. Clinical liver water-fat imaging typically requires breath-hold acquisitions, with the free-breathing acquisition method being more desirable for patient comfort. However, the acquisition for free-breathing imaging could take up to several minutes. The purpose of this study is to accelerate four-dimensional free-breathing whole-liver water-fat MRI by jointly using high-dimensional deep dictionary learning and model-guided (MG) reconstruction. Methods A high-dimensional model-guided deep dictionary learning (HMDDL) algorithm is proposed for the acceleration. The HMDDL combines the powers of the high-dimensional dictionary learning neural network (hdDLNN) and the chemical shift model. The neural network utilizes the prior information of the dynamic multi-echo data in spatial respiratory motion, and echo dimensions to exploit the features of images. The chemical shift model is used to guide the reconstruction of field maps, R 2 ∗ maps, water images, and fat images. Data acquired from ten healthy subjects and ten subjects with clinically diagnosed nonalcoholic fatty liver disease (NAFLD) were selected for training. Data acquired from one healthy subject and two NAFLD subjects were selected for validation. Data acquired from five healthy subjects and five NAFLD subjects were selected for testing. A three-dimensional (3D) blipped golden-angle stack-of-stars multi-gradient-echo pulse sequence was designed to accelerate the data acquisition. The retrospectively undersampled data were used for training, and the prospectively undersampled data were used for testing. The performance of the HMDDL was evaluated in comparison with the compressed sensing-based water-fat separation (CS-WF) algorithm and a parallel non-Cartesian recurrent neural network (PNCRNN) algorithm. Results Four-dimensional water-fat images with ten motion states for whole-liver are demonstrated at several R values. In comparison with the CS-WF and PNCRNN, the HMDDL improved the mean peak signal-to-noise ratio (PSNR) of images by 9.93 and 2.20 dB, respectively, and improved the mean structure similarity (SSIM) of images by 0.058 and 0.009, respectively, at R=10. The paired t-test shows that there was no significant difference between HMDDL and ground truth for proton-density fat fraction (PDFF) and R 2 ∗ values at R up to 10. Conclusions The proposed HMDDL enables features of water images and fat images from the highly undersampled multi-echo data along spatial, respiratory motion, and echo dimensions, to improve the performance of accelerated four-dimensional (4D) free-breathing water-fat imaging.
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Affiliation(s)
- Shuo Li
- National Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Zhijun Wang
- National Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Zekang Ding
- National Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Huajun She
- National Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Yiping P Du
- National Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
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11
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Jeon KJ, Choi YJ, Lee C, Kim HS, Han SS. Evaluation of masticatory muscles in temporomandibular joint disorder patients using quantitative MRI fat fraction analysis-Could it be a biomarker? PLoS One 2024; 19:e0296769. [PMID: 38241266 PMCID: PMC10798479 DOI: 10.1371/journal.pone.0296769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 12/18/2023] [Indexed: 01/21/2024] Open
Abstract
Temporomandibular joint disorders (TMDs) are closely related to the masticatory muscles, but objective and quantitative methods to evaluate muscle are lacking. IDEAL-IQ, a type of chemical shift-encoded magnetic resonance imaging (CSE-MRI), can quantify the fat fraction (FF). The purpose of this study was to develop an MR IDEAL-IQ-based method for quantitative muscle diagnosis in TMD patients. A total of 65 patients who underwent 3 T MRI scans, including CSE-MRI sequences, were retrospectively included. MRI diagnoses and clinical data were reviewed. There were 19 patients in the normal group and 46 patients in the TMD group with unilateral disc displacement. The TMD group was subdivided into those with and without clenching. The right and left FF values of the masseter, medial, and lateral pterygoid muscles were measured twice by two oral radiologists on CSE-MRI, and the average value was used. FF measurements using CSE-MRI showed excellent intra- and inter-observer agreement (ICC > 0.889 for both). There were no statistically significant differences between the right and left FF values in the masseter, medial pterygoid, and lateral pterygoid of the normal group (p > 0.05). A statistically significant difference was found in the TMD group without clenching, in which the masseter muscle had a statistically significantly lower FF value on the disc displacement side (3.94 ± 1.61) than on the normal side (4.52 ± 2.24) (p < 0.05). CSE-MRI, which can reproducibly quantify muscle FF values, is expected to be a biomarker for objective muscle evaluation in TMD patients. The masseter muscle is expected to be particularly useful compared to other masticatory muscles, but further research is needed.
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Affiliation(s)
- Kug Jin Jeon
- Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, Seoul, Republic of Korea
| | - Yoon Joo Choi
- Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, Seoul, Republic of Korea
| | - Chena Lee
- Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, Seoul, Republic of Korea
| | - Hak-Sun Kim
- Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, Seoul, Republic of Korea
| | - Sang-Sun Han
- Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, Seoul, Republic of Korea
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12
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Wang X, Pan X, Zhou W, Jing Z, Yu F, Wang Y, Zeng J, Wu J, Zeng X, Zhang J. Quantification of Hepatic Steatosis on Dual-Energy CT in Comparison With MRI mDIXON-Quant Sequence in Breast Cancer. J Comput Assist Tomogr 2024; 48:64-71. [PMID: 37558648 DOI: 10.1097/rct.0000000000001529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/11/2023]
Abstract
OBJECTIVE The study aimed to evaluate the correlation and diagnostic value of liver fat quantification in unenhanced dual-energy CT (DECT) using quantitative magnetic resonance imaging (MRI) mDIXON-Quant sequence as reference standard in patients with breast cancer. METHODS Patients with breast cancer were prospectively recruited between June 2018 and April 2020. Each patient underwent liver DECT and MRI mDIXON-Quant examination. The DECT-fat volume fraction (FVF) and liver-spleen attenuation differences were compared with the MRI-proton density fat fraction using scatterplots, Bland-Altman plots, and concordance correlation coefficient. Receiver operating characteristic curves were established to determine the diagnostic accuracy of hepatic steatosis by DECT. RESULTS A total of 216 patients with breast cancer (mean age, 50.08 ± 9.33 years) were evaluated. The DECT-FVF correlated well with MRI-proton density fat fraction ( r2 = 0.902; P < 0.001), which was higher than the difference in liver-spleen attenuation ( r2 = 0.728; P < 0.001). Bland-Altman analysis revealed slight positive bias; the mean difference was 3.986. The DECT-FVF yielded an average concordance correlation coefficient of 0.677, which was higher than the difference of liver-spleen attenuation (-0.544). The DECT-FVF and the difference in liver-spleen attenuation both lead to mild overestimation of hepatic steatosis. The areas under the curve of DECT-FVF (0.956) were higher than the difference in liver-spleen attenuation (0.807) in identifying hepatic steatosis ( P < 0.001). CONCLUSIONS Dual-energy CT-FVF may serve as a reliable screening and quantitative tool for hepatic steatosis in patients with breast cancer.
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Affiliation(s)
- Xiaoxia Wang
- From the Department of Radiology, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC)
| | - Xianjun Pan
- Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing
| | - Wenqi Zhou
- Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing
| | - Zhouhong Jing
- Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing
| | - Feng Yu
- Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing
| | - Yali Wang
- Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing
| | - Junjie Zeng
- Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing
| | | | - Xiaohua Zeng
- Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing
| | - Jiuquan Zhang
- From the Department of Radiology, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC)
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Boeriu A, Dobru D, Fofiu C. Non-Invasive Diagnostic of NAFLD in Type 2 Diabetes Mellitus and Risk Stratification: Strengths and Limitations. Life (Basel) 2023; 13:2262. [PMID: 38137863 PMCID: PMC10744403 DOI: 10.3390/life13122262] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Revised: 10/26/2023] [Accepted: 11/25/2023] [Indexed: 12/24/2023] Open
Abstract
The progressive potential of liver damage in type 2 diabetes mellitus (T2DM) towards advanced fibrosis, end-stage liver disease, and hepatocarcinoma has led to increased concern for quantifying liver injury and individual risk assessment. The combination of blood-based markers and imaging techniques is recommended for the initial evaluation in NAFLD and for regular monitoring to evaluate disease progression. Continued development of ultrasonographic and magnetic resonance imaging methods for accurate quantification of liver steatosis and fibrosis, as well as promising tools for the detection of high-risk NASH, have been noted. In this review, we aim to summarize available evidence regarding the usefulness of non-invasive methods for the assessment of NAFLD in T2DM. We focus on the power and limitations of various methods for diagnosis, risk stratification, and patient monitoring that support their implementation in clinical setting or in research field.
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Affiliation(s)
- Alina Boeriu
- Gastroenterology Department, University of Medicine Pharmacy, Sciences, and Technology “George Emil Palade” Targu Mures, 540142 Targu Mures, Romania;
- Gastroenterology Department, Mures County Clinical Hospital, 540103 Targu Mures, Romania
| | - Daniela Dobru
- Gastroenterology Department, University of Medicine Pharmacy, Sciences, and Technology “George Emil Palade” Targu Mures, 540142 Targu Mures, Romania;
- Gastroenterology Department, Mures County Clinical Hospital, 540103 Targu Mures, Romania
| | - Crina Fofiu
- Gastroenterology Department, University of Medicine Pharmacy, Sciences, and Technology “George Emil Palade” Targu Mures, 540142 Targu Mures, Romania;
- Internal Medicine Department, Bistrita County Clinical Hospital, 420094 Bistrita, Romania
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14
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Wang K, Cunha GM, Hasenstab K, Henderson WC, Middleton MS, Cole SA, Umans JG, Ali T, Hsiao A, Sirlin CB. Deep Learning for Inference of Hepatic Proton Density Fat Fraction From T1-Weighted In-Phase and Opposed-Phase MRI: Retrospective Analysis of Population-Based Trial Data. AJR Am J Roentgenol 2023; 221:620-631. [PMID: 37466189 DOI: 10.2214/ajr.23.29607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/20/2023]
Abstract
BACKGROUND. The confounder-corrected chemical shift-encoded MRI (CSE-MRI) sequence used to determine proton density fat fraction (PDFF) for hepatic fat quantification is not widely available. As an alternative, hepatic fat can be assessed by a two-point Dixon method to calculate signal fat fraction (FF) from conventional T1-weighted in- and opposed-phase (IOP) images, although signal FF is prone to biases, leading to inaccurate quantification. OBJECTIVE. The purpose of this study was to compare hepatic fat quantification by use of PDFF inferred from conventional T1-weighted IOP images and deep-learning convolutional neural networks (CNNs) with quantification by use of two-point Dixon signal FF with CSE-MRI PDFF as the reference standard. METHODS. This study entailed retrospective analysis of data from 292 participants (203 women, 89 men; mean age, 53.7 ± 12.0 [SD] years) enrolled at two sites from September 1, 2017, to December 18, 2019, in the Strong Heart Family Study (a prospective population-based study of American Indian communities). Participants underwent liver MRI (site A, 3 T; site B, 1.5 T) including T1-weighted IOP MRI and CSE-MRI (used to reconstruct CSE PDFF and CSE R2* maps). With CSE PDFF as reference, a CNN was trained in a random sample of 218 (75%) participants to infer voxel-by-voxel PDFF maps from T1-weighted IOP images; testing was performed in the other 74 (25%) participants. Parametric values from the entire liver were automatically extracted. Per-participant median CNN-inferred PDFF and median two-point Dixon signal FF were compared with reference median CSE-MRI PDFF by means of linear regression analysis, intraclass correlation coefficient (ICC), and Bland-Altman analysis. The code is publicly available at github.com/kang927/CNN-inference-of-PDFF-from-T1w-IOP-MR. RESULTS. In the 74 test-set participants, reference CSE PDFF ranged from 1% to 32% (mean, 11.3% ± 8.3% [SD]); reference CSE R2* ranged from 31 to 457 seconds-1 (mean, 62.4 ± 67.3 seconds-1 [SD]). Agreement metrics with reference to CSE PDFF for CNN-inferred PDFF were ICC = 0.99, bias = -0.19%, 95% limits of agreement (LoA) = (-2.80%, 2.71%) and for two-point Dixon signal FF were ICC = 0.93, bias = -1.11%, LoA = (-7.54%, 5.33%). CONCLUSION. Agreement with reference CSE PDFF was better for CNN-inferred PDFF from conventional T1-weighted IOP images than for two-point Dixon signal FF. Further investigation is needed in individuals with moderate-to-severe iron overload. CLINICAL IMPACT. Measurement of CNN-inferred PDFF from widely available T1-weighted IOP images may facilitate adoption of hepatic PDFF as a quantitative bio-marker for liver fat assessment, expanding opportunities to screen for hepatic steatosis and nonalcoholic fatty liver disease.
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Affiliation(s)
- Kang Wang
- Department of Radiology, Artificial Intelligence and Data Analytic Laboratory, University of California, San Diego, La Jolla, CA
- Department of Radiology, Liver Imaging Group, University of California, San Diego, La Jolla, CA
- Department of Radiology, Stanford University, 500 Pasteur Dr, Palo Alto, CA 94304
| | | | - Kyle Hasenstab
- Department of Radiology, Artificial Intelligence and Data Analytic Laboratory, University of California, San Diego, La Jolla, CA
- Department of Radiology, Liver Imaging Group, University of California, San Diego, La Jolla, CA
- Department of Mathematics and Statistics, San Diego State University, San Diego, CA
| | - Walter C Henderson
- Department of Radiology, Liver Imaging Group, University of California, San Diego, La Jolla, CA
| | - Michael S Middleton
- Department of Radiology, Liver Imaging Group, University of California, San Diego, La Jolla, CA
| | - Shelley A Cole
- Population Health, Texas Biomedical Research Institute, San Antonio, TX
| | - Jason G Umans
- MedStar Health Research Institute, Field Studies Division, Hyattsville, MD
- Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC
| | - Tauqeer Ali
- Department of Biostatistics and Epidemiology, Center for American Indian Health Research, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK
| | - Albert Hsiao
- Department of Radiology, Artificial Intelligence and Data Analytic Laboratory, University of California, San Diego, La Jolla, CA
| | - Claude B Sirlin
- Department of Radiology, Liver Imaging Group, University of California, San Diego, La Jolla, CA
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15
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Tsujita Y, Sofue K, Ueshima E, Ueno Y, Hori M, Murakami T. Clinical Application of Quantitative MR Imaging in Nonalcoholic Fatty Liver Disease. Magn Reson Med Sci 2023; 22:435-445. [PMID: 35584952 PMCID: PMC10552668 DOI: 10.2463/mrms.rev.2021-0152] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 03/23/2022] [Indexed: 11/09/2022] Open
Abstract
Viral hepatitis was previously the most common cause of chronic liver disease. However, in recent years, nonalcoholic fatty liver disease (NAFLD) cases have been increasing, especially in developed countries. NAFLD is histologically characterized by fat, fibrosis, and inflammation in the liver, eventually leading to cirrhosis and hepatocellular carcinoma. Although biopsy is the gold standard for the assessment of the liver parenchyma, quantitative evaluation methods, such as ultrasound, CT, and MRI, have been reported to have good diagnostic performances. The quantification of liver fat, fibrosis, and inflammation is expected to be clinically useful in terms of the prognosis, early intervention, and treatment response for the management of NAFLD. The aim of this review was to discuss the basics and prospects of MRI-based tissue quantifications of the liver, mainly focusing on proton density fat fraction for the quantification of fat deposition, MR elastography for the quantification of fibrosis, and multifrequency MR elastography for the evaluation of inflammation.
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Affiliation(s)
- Yushi Tsujita
- Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan
| | - Keitaro Sofue
- Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan
| | - Eisuke Ueshima
- Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan
| | - Yoshiko Ueno
- Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan
| | - Masatoshi Hori
- Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan
| | - Takamichi Murakami
- Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan
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Tian Y, Liu PF, Li JY, Li YN, Sun P. Hepatic MR imaging using IDEAL-IQ sequence: Will Gd-EOB-DTPA interfere with reproductivity of fat fraction quantification? World J Clin Cases 2023; 11:5887-5896. [PMID: 37727487 PMCID: PMC10506030 DOI: 10.12998/wjcc.v11.i25.5887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 05/31/2023] [Accepted: 07/14/2023] [Indexed: 09/01/2023] Open
Abstract
BACKGROUND Iterative decomposition of water and fat with echo asymmetry and least squares estimation quantification sequence (IDEAL-IQ) is based on chemical shift-based water and fat separation technique to get proton density fat fraction. Multiple studies have shown that using IDEAL-IQ to test the stability and repeatability of liver fat is acceptable and has high accuracy. AIM To explore whether Gadoxetate Disodium (Gd-EOB-DTPA) interferes with the measurement of the hepatic fat content quantified with the IDEAL-IQ and to evaluate the robustness of this technique. METHODS IDEAL-IQ was used to quantify the liver fat content at 3.0T in 65 patients injected with Gd-EOB-DTPA contrast. After injection, IDEAL-IQ was estimated four times, and the fat fraction (FF) and R2* were measured at the following time points: Pre-contrast, between the portal phase (70 s) and the late phase (180 s), the delayed phase (5 min) and the hepatobiliary phase (20 min). One-way repeated-measures analysis was conducted to evaluate the difference in the FFs between the four time points. Bland-Altman plots were adopted to assess the FF changes before and after injection of the contrast agent. P < 0.05 was considered statistically significant. RESULTS The assessment of the FF at the four time points in the liver, spleen and spine showed no significant differences, and the measurements of hepatic FF yielded good consistency between T1 and T2 [95% confidence interval: -0.6768%, 0.6658%], T1 and T3 (-0.3900%, 0.3178%), and T1 and T4 (-0.3750%, 0.2825%). R2* of the liver, spleen and spine increased significantly after injection (P < 0.0001). CONCLUSION Using the IDEAL-IQ sequence to measure the FF, we can obtain results that will not be affected by Gd-EOB-DTPA. The high reproducibility of the IDEAL-IQ sequence makes it available in the scanning interval to save time during multiphase examinations.
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Affiliation(s)
- Yuan Tian
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Harbin Medical University, Harbin 150001, Heilongjiang Province, China
| | - Peng-Fei Liu
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Harbin Medical University, Harbin 150001, Heilongjiang Province, China
| | - Jia-Yu Li
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Harbin Medical University, Harbin 150001, Heilongjiang Province, China
| | - Ya-Nan Li
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Harbin Medical University, Harbin 150001, Heilongjiang Province, China
| | - Peng Sun
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Harbin Medical University, Harbin 150001, Heilongjiang Province, China
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Kuo SZ, Cepin S, Bergstrom J, Siddiqi H, Jung J, Lopez S, Huang DQ, Taub P, Amangurbanova M, Loomba R. Clinical utility of liver fat quantification for determining cardiovascular disease risk among patients with type 2 diabetes. Aliment Pharmacol Ther 2023; 58:585-592. [PMID: 37431679 PMCID: PMC10792531 DOI: 10.1111/apt.17637] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Revised: 12/27/2022] [Accepted: 06/27/2023] [Indexed: 07/12/2023]
Abstract
BACKGROUND Nonalcoholic fatty liver disease (NAFLD) and type 2 diabetes mellitus (T2DM) are independent risk factors for cardiovascular disease (CVD). AIMS To examine the clinical utility of liver fat quantification for determining CVD risk among a well-phenotyped cohort of patients with T2DM. METHODS This was a cross-sectional analysis of a prospective cohort of adults aged ≥50 with T2DM. Liver fat was quantified with magnetic resonance imaging proton-density-fat-fraction (MRI-PDFF), an advanced imaging-based biomarker. Patients were stratified into a higher liver fat group (MRI-PDFF ≥ 14.6%), and a lower liver fat group (MRI-PDFF < 14.6%). The co-primary outcomes were CVD risk determined by Framingham and Atherosclerotic Cardiovascular Disease (ASCVD) risk scores. High CVD risk was defined by risk scores ≥20%. RESULTS Of the 391 adults (66% female) in this study, the mean (±SD) age was 64 (±8) years and BMI 30.8 (±5.2) kg/m2 , respectively. In multivariable analysis, adjusted for age, gender, race, and BMI, patients in the higher liver fat group had higher CVD risk [OR = 4.04 (95% CI: 2.07-7.88, p < 0.0001)] and ASCVD risk score [OR = 2.85 (95% CI: 1.19-6.83, p = 0.018)], respectively. CONCLUSION Higher liver fat content increases CVD risk independently of age, gender, ethnicity and BMI. These findings raise the question whether liver fat quantification should be incorporated into risk calculators to further stratify those with higher CVD risk.
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Affiliation(s)
- Selena Z. Kuo
- NAFLD Research Center, Division of Gastroenterology, University of California at San Diego, La Jolla, California, USA
- Division of Gastroenterology, University of California at San Diego, La Jolla, California, USA
| | - Sandra Cepin
- NAFLD Research Center, Division of Gastroenterology, University of California at San Diego, La Jolla, California, USA
| | - Jaclyn Bergstrom
- NAFLD Research Center, Division of Gastroenterology, University of California at San Diego, La Jolla, California, USA
| | - Harris Siddiqi
- NAFLD Research Center, Division of Gastroenterology, University of California at San Diego, La Jolla, California, USA
| | - Jinho Jung
- NAFLD Research Center, Division of Gastroenterology, University of California at San Diego, La Jolla, California, USA
| | - Scarlett Lopez
- NAFLD Research Center, Division of Gastroenterology, University of California at San Diego, La Jolla, California, USA
| | - Daniel Q. Huang
- NAFLD Research Center, Division of Gastroenterology, University of California at San Diego, La Jolla, California, USA
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Division of Gastroenterology and Hepatology, Department of Medicine, National University Health System, Singapore, Singapore
| | - Pam Taub
- Division of Cardiovascular Medicine, Department of Medicine, University of California at San Diego, La Jolla, California, USA
| | - Maral Amangurbanova
- NAFLD Research Center, Division of Gastroenterology, University of California at San Diego, La Jolla, California, USA
| | - Rohit Loomba
- NAFLD Research Center, Division of Gastroenterology, University of California at San Diego, La Jolla, California, USA
- Division of Gastroenterology, University of California at San Diego, La Jolla, California, USA
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Jang W, Song JS. Non-Invasive Imaging Methods to Evaluate Non-Alcoholic Fatty Liver Disease with Fat Quantification: A Review. Diagnostics (Basel) 2023; 13:diagnostics13111852. [PMID: 37296703 DOI: 10.3390/diagnostics13111852] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Revised: 05/17/2023] [Accepted: 05/23/2023] [Indexed: 06/12/2023] Open
Abstract
Hepatic steatosis without specific causes (e.g., viral infection, alcohol abuse, etc.) is called non-alcoholic fatty liver disease (NAFLD), which ranges from non-alcoholic fatty liver (NAFL) to non-alcoholic steatohepatitis (NASH), fibrosis, and NASH-related cirrhosis. Despite the usefulness of the standard grading system, liver biopsy has several limitations. In addition, patient acceptability and intra- and inter-observer reproducibility are also concerns. Due to the prevalence of NAFLD and limitations of liver biopsies, non-invasive imaging methods such as ultrasonography (US), computed tomography (CT), and magnetic resonance imaging (MRI) that can reliably diagnose hepatic steatosis have developed rapidly. US is widely available and radiation-free but cannot examine the entire liver. CT is readily available and helpful for detection and risk classification, significantly when analyzed using artificial intelligence; however, it exposes users to radiation. Although expensive and time-consuming, MRI can measure liver fat percentage with magnetic resonance imaging proton density fat fraction (MRI-PDFF). Specifically, chemical shift-encoded (CSE)-MRI is the best imaging indicator for early liver fat detection. The purpose of this review is to provide an overview of each imaging modality with an emphasis on the recent progress and current status of liver fat quantification.
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Affiliation(s)
- Weon Jang
- Department of Radiology, Jeonbuk National University Medical School and Hospital, 20 Geonji-ro, Deokjin-gu, Jeonju 54907, Jeonbuk, Republic of Korea
- Research Institute of Clinical Medicine, Jeonbuk National University, Jeonju 54907, Jeonbuk, Republic of Korea
- Biomedical Research Institute, Jeonbuk National University Hospital, Jeonju 54907, Jeonbuk, Republic of Korea
| | - Ji Soo Song
- Department of Radiology, Jeonbuk National University Medical School and Hospital, 20 Geonji-ro, Deokjin-gu, Jeonju 54907, Jeonbuk, Republic of Korea
- Research Institute of Clinical Medicine, Jeonbuk National University, Jeonju 54907, Jeonbuk, Republic of Korea
- Biomedical Research Institute, Jeonbuk National University Hospital, Jeonju 54907, Jeonbuk, Republic of Korea
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Jeon KJ, Park Y, Jeong H, Lee C, Choi YJ, Han SS. Parotid gland evaluation of menopausal women with xerostomia using the iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL-IQ) method of MRI: a pilot study. Dentomaxillofac Radiol 2023; 52:20220349. [PMID: 36695352 PMCID: PMC10170170 DOI: 10.1259/dmfr.20220349] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 12/25/2022] [Accepted: 01/11/2023] [Indexed: 01/26/2023] Open
Abstract
OBJECTIVES This study aimed to analyze the quantitative fat fraction (FF) of the parotid gland in menopausal females with xerostomia using the iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL-IQ) method. METHODS A total 138 parotid glands of 69 menopausal females were enrolled in our study and participants were divided into normal group and xerostomia group. The xerostomia group was divided into those with or without Sjögren's syndrome. Participants underwent IDEAL-IQ sequences of MRI and the stimulated salivary flow test (s-SFR). The unpaired t-test was used to compare the FFs between the normal and xerostomia groups and between the subgroups with and without Sjögren's syndrome. The correlation between FF and s-SFR was analyzed by Pearson's correlation. RESULTS Excellent intra- and interobserver agreement during the measurement of FFs by IDEAL-IQ method (ICC>0.99, respectively). FF value in the xerostomia group was statistically significantly higher than the value in the normal group (p < 0.05). Within the xerostomia group, the average FF value of females with Sjögren's syndrome was higher than that of females without Sjögren's syndrome. However, the difference was not statistically significant (p > 0.05). Within the xerostomia group, FF value correlated negatively with s-SFR (p < 0.05). CONCLUSIONS The FF of the parotid gland was higher in the xerostomia group than in the normal group and FF value and s-SFR showed a negative correlation. Analyses of the FF using IDEAL-IQ in menopausal females can be helpful for the quantitative diagnosis of xerostomia.
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Affiliation(s)
- Kug Jin Jeon
- Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, Seoul, Republic of Korea
| | - Younjung Park
- Department of Orofacial Pain and Oral Medicine, Yonsei Dental Hospital, Yonsei University College of Dentistry, Seoul, Republic of Korea
| | - Hui Jeong
- Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, Seoul, Republic of Korea
| | - Chena Lee
- Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, Seoul, Republic of Korea
| | - Yoon Joo Choi
- Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, Seoul, Republic of Korea
| | - Sang-Sun Han
- Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, Seoul, Republic of Korea
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20
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Age and gender differences in vertebral bone marrow adipose tissue and bone mineral density, based on MRI and quantitative CT. Eur J Radiol 2023; 159:110669. [PMID: 36608598 DOI: 10.1016/j.ejrad.2022.110669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 12/20/2022] [Accepted: 12/22/2022] [Indexed: 12/25/2022]
Abstract
PURPOSE To investigate the age and gender differences in vertebral bone marrow adipose tissue (BMAT) and volumetric bone mineral density (vBMD). METHOD A total of 427 healthy adults, including 175 males (41 %) and 252 females (59 %) with an age range of 21-82 years, underwent MRI and quantitative CT examinations of the lumbar spine (L2-L4), and the corresponding BMAT and vBMD values were measured. The age-related progressions of BMAT and vBMD in men and women were evaluated and compared. RESULTS In males, vertebral BMAT rose gradually throughout life, while in females, BMAT increased sharply between 41 and 60 years of age. In participants aged < 40 years, BMAT was greater in males compared to females (p ≤ 0.01), while after the age of 60, BMAT was higher in females (p < 0.05). In males, vBMD decreased gradually with age, while in females, there was a sharp decrease in vBMD after the age of 40 years. At age of 31-40 years, vBMD was higher in females (P < 0.002), while at age > 60 years, vBMD was higher in males (61-70 years, P < 0.01; > 70 years, P = 0.02). CONCLUSIONS We found significant age and gender differences in lumbar BMAT and vBMD. These findings will help to improve our understanding of the interaction between bone marrow fat content and bone mineral density in the ageing process.
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21
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Hernando D, Zhao R, Yuan Q, Aliyari Ghasabeh M, Ruschke S, Miao X, Karampinos DC, Mao L, Harris DT, Mattison RJ, Jeng MR, Pedrosa I, Kamel IR, Vasanawala S, Yokoo T, Reeder SB. Multicenter Reproducibility of Liver Iron Quantification with 1.5-T and 3.0-T MRI. Radiology 2023; 306:e213256. [PMID: 36194113 PMCID: PMC9885339 DOI: 10.1148/radiol.213256] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 07/22/2022] [Accepted: 08/08/2022] [Indexed: 01/26/2023]
Abstract
Background MRI is a standard of care tool to measure liver iron concentration (LIC). Compared with regulatory-approved R2 MRI, R2* MRI has superior speed and is available in most MRI scanners; however, the cross-vendor reproducibility of R2*-based LIC estimation remains unknown. Purpose To evaluate the reproducibility of LIC via single-breath-hold R2* MRI at both 1.5 T and 3.0 T with use of a multicenter, multivendor study. Materials and Methods Four academic medical centers using MRI scanners from three different vendors (three 1.5-T scanners, one 2.89-T scanner, and two 3.0-T scanners) participated in this prospective cross-sectional study. Participants with known or suspected liver iron overload were recruited to undergo multiecho gradient-echo MRI for R2* mapping at 1.5 T and 3.0 T (2.89 T or 3.0 T) on the same day. R2* maps were reconstructed from the multiecho images and analyzed at a single center. Reference LIC measurements were obtained with a commercial R2 MRI method performed using standardized 1.5-T spin-echo imaging. R2*-versus-LIC calibrations were generated across centers and field strengths using linear regression and compared using F tests. Receiver operating characteristic (ROC) curve analysis was used to determine the diagnostic performance of R2* MRI in the detection of clinically relevant LIC thresholds. Results A total of 207 participants (mean age, 38 years ± 20 [SD]; 117 male participants) were evaluated between March 2015 and September 2019. A linear relationship was confirmed between R2* and LIC. All calibrations within the same field strength were highly reproducible, showing no evidence of statistically significant center-specific differences (P > .43 across all comparisons). Calibrations for 1.5 T and 3.0 T were generated, as follows: for 1.5 T, LIC (in milligrams per gram [dry weight]) = -0.16 + 2.603 × 10-2 R2* (in seconds-1); for 2.89 T, LIC (in milligrams per gram) = -0.03 + 1.400 × 10-2 R2* (in seconds-1); for 3.0 T, LIC (in milligrams per gram) = -0.03 + 1.349 × 10-2 R2* (in seconds-1). Liver R2* had high diagnostic performance in the detection of clinically relevant LIC thresholds (area under the ROC curve, >0.98). Conclusion R2* MRI enabled accurate and reproducible quantification of liver iron overload over clinically relevant ranges of liver iron concentration (LIC). The data generated in this study provide the necessary calibrations for broad clinical dissemination of R2*-based LIC quantification. ClinicalTrials.gov registration no.: NCT02025543 © RSNA, 2022 Online supplemental material is available for this article.
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Affiliation(s)
- Diego Hernando
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - Ruiyang Zhao
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - Qing Yuan
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - Mounes Aliyari Ghasabeh
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - Stefan Ruschke
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - Xinran Miao
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - Dimitrios C. Karampinos
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - Lu Mao
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - David T. Harris
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - Ryan J. Mattison
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - Michael R. Jeng
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - Ivan Pedrosa
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - Ihab R. Kamel
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - Shreyas Vasanawala
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - Takeshi Yokoo
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - Scott B. Reeder
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
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22
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Yi J, Xu F, Li T, Liang B, Li S, Feng Q, Long L. Quantitative study of 3T MRI qDixon-WIP applied in pancreatic fat infiltration in patients with type 2 diabetes mellitus. Front Endocrinol (Lausanne) 2023; 14:1140111. [PMID: 36875489 PMCID: PMC9981945 DOI: 10.3389/fendo.2023.1140111] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Accepted: 02/02/2023] [Indexed: 02/19/2023] Open
Abstract
OBJECTIVE To investigate the application value of 3T MRI qDixon-WIP technique in the quantitative measurement of pancreatic fat content in patients with type 2 diabetes mellitus (T2DM). METHODS The 3T MRI qDixon-WIP sequence was used to scan the livers and the pancreas of 47 T2DM patients (experimental group) and 48 healthy volunteers (control group). Pancreatic fat fraction (PFF), hepatic fat fraction (HFF), Body mass index (BMI) ratio of pancreatic volume to body surface area (PVI) were measured. Total cholesterol (TC), subcutaneous fat area (SA), triglyceride (TG), abdominal visceral fat area (VA), high density lipoprotein (HDL-c), fasting blood glucose (FPC) and low-density lipoprotein (LDL-c) were collected. The relationship between the experimental group and the control group and between PFF and other indicators was compared. The differences of PFF between the control group and different disease course subgroups were also explored. RESULTS There was no significant difference in BMI between the experimental group and the control group (P=0.231). PVI, SA, VA, PFF and HFF had statistical differences (P<0.05). In the experimental group, PFF was highly positively correlated with HFF (r=0.964, P<0.001), it was moderately positively correlated with TG and abdominal fat area (r=0.676, 0.591, P<0.001), and it was weakly positively correlated with subcutaneous fat area (r=0.321, P=0.033). And it had no correlation with FPC, PVI, HDL-c, TC and LDL-c (P>0.05). There were statistical differences in PFF between the control group and the patients with different course of T2DM (P<0.05). There was no significant difference in PFF between T2DM patients with a disease course ≤1 year and those with a disease course <5 years (P>0.05). There were significant differences in PFF between the groups with a disease course of 1-5 years and those with a disease course of more than 5 years (P<0.001). CONCLUSION PVI of T2DM patients is lower than normal, but SA, VA, PFF, HFF are higher than normal. The degree of pancreatic fat accumulation in T2DM patients with long disease course was higher than that in patients with short disease course. The qDixon-WIP sequence can provide an important reference for clinical quantitative evaluation of fat content in T2DM patients.
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Affiliation(s)
- Jixing Yi
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Guangxi Zhuang Autonomous Region, Nanning, China
- Department of Radiology, Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou Worker’s Hospital Guangxi Zhuang Autonomous Region, Liuzhou, China
| | - Fengming Xu
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Guangxi Zhuang Autonomous Region, Nanning, China
| | - Tao Li
- Department of Radiology, Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou Worker’s Hospital Guangxi Zhuang Autonomous Region, Liuzhou, China
| | - Bumin Liang
- School of International Education, Guangxi Medical University, Guangxi Zhuang Autonomous Region, Nanning, China
| | - Shu Li
- Department of Radiology, Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou Worker’s Hospital Guangxi Zhuang Autonomous Region, Liuzhou, China
| | - Qing Feng
- Department of Radiology, Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou Worker’s Hospital Guangxi Zhuang Autonomous Region, Liuzhou, China
| | - Liling Long
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Guangxi Zhuang Autonomous Region, Nanning, China
- *Correspondence: Liling Long,
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Updates on Quantitative MRI of Diffuse Liver Disease: A Narrative Review. BIOMED RESEARCH INTERNATIONAL 2022; 2022:1147111. [PMID: 36619303 PMCID: PMC9812615 DOI: 10.1155/2022/1147111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 12/10/2022] [Accepted: 12/12/2022] [Indexed: 12/29/2022]
Abstract
Diffuse liver diseases are highly prevalent conditions around the world, including pathological liver changes that occur when hepatocytes are damaged and liver function declines, often leading to a chronic condition. In the last years, Magnetic Resonance Imaging (MRI) is reaching an important role in the study of diffuse liver diseases moving from qualitative to quantitative assessment of liver parenchyma. In fact, this can allow noninvasive accurate and standardized assessment of diffuse liver diseases and can represent a concrete alternative to biopsy which represents the current reference standard. MRI approach already tested for other pathologies include diffusion-weighted imaging (DWI) and radiomics, able to quantify different aspects of diffuse liver disease. New emerging MRI quantitative methods include MR elastography (MRE) for the quantification of the hepatic stiffness in cirrhotic patients, dedicated gradient multiecho sequences for the assessment of hepatic fat storage, and iron overload. Thus, the aim of this review is to give an overview of the technical principles and clinical application of new quantitative MRI techniques for the evaluation of diffuse liver disease.
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Assessing breast density using the chemical-shift encoding-based proton density fat fraction in 3-T MRI. Eur Radiol 2022; 33:3810-3818. [PMID: 36538074 PMCID: PMC10182116 DOI: 10.1007/s00330-022-09341-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 11/22/2022] [Accepted: 11/29/2022] [Indexed: 12/24/2022]
Abstract
Abstract
Objectives
There is a clinical need for a non-ionizing, quantitative assessment of breast density, as one of the strongest independent risk factors for breast cancer. This study aims to establish proton density fat fraction (PDFF) as a quantitative biomarker for fat tissue concentration in breast MRI and correlate mean breast PDFF to mammography.
Methods
In this retrospective study, 193 women were routinely subjected to 3-T MRI using a six-echo chemical shift encoding-based water-fat sequence. Water-fat separation was based on a signal model accounting for a single T2* decay and a pre-calibrated 7-peak fat spectrum resulting in volumetric fat-only, water-only images, PDFF- and T2*-values. After semi-automated breast segmentation, PDFF and T2* values were determined for the entire breast and fibroglandular tissue. The mammographic and MRI-based breast density was classified by visual estimation using the American College of Radiology Breast Imaging Reporting and Data System categories (ACR A-D).
Results
The PDFF negatively correlated with mammographic and MRI breast density measurements (Spearman rho: −0.74, p < .001) and revealed a significant distinction between all four ACR categories. Mean T2* of the fibroglandular tissue correlated with increasing ACR categories (Spearman rho: 0.34, p < .001). The PDFF of the fibroglandular tissue showed a correlation with age (Pearson rho: 0.56, p = .03).
Conclusion
The proposed breast PDFF as an automated tissue fat concentration measurement is comparable with mammographic breast density estimations. Therefore, it is a promising approach to an accurate, user-independent, and non-ionizing breast density assessment that could be easily incorporated into clinical routine breast MRI exams.
Key Points
• The proposed PDFF strongly negatively correlates with visually determined mammographic and MRI-based breast density estimations and therefore allows for an accurate, non-ionizing, and user-independent breast density measurement.
• In combination with T2*, the PDFF can be used to track structural alterations in the composition of breast tissue for an individualized risk assessment for breast cancer.
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Park S, Kwon JH, Kim SY, Kang JH, Chung JI, Jang JK, Jang HY, Shim JH, Lee SS, Kim KW, Song GW. Cutoff Values for Diagnosing Hepatic Steatosis Using Contemporary MRI-Proton Density Fat Fraction Measuring Methods. Korean J Radiol 2022; 23:1260-1268. [PMID: 36447414 PMCID: PMC9747271 DOI: 10.3348/kjr.2022.0334] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 09/06/2022] [Accepted: 09/27/2022] [Indexed: 11/11/2022] Open
Abstract
OBJECTIVE To propose standardized MRI-proton density fat fraction (PDFF) cutoff values for diagnosing hepatic steatosis, evaluated using contemporary PDFF measuring methods in a large population of healthy adults, using histologic fat fraction (HFF) as the reference standard. MATERIALS AND METHODS A retrospective search of electronic medical records between 2015 and 2018 identified 1063 adult donor candidates for liver transplantation who had undergone liver MRI and liver biopsy within a 7-day interval. Patients with a history of liver disease or significant alcohol consumption were excluded. Chemical shift imaging-based MRI (CS-MRI) PDFF and high-speed T2-corrected multi-echo MR spectroscopy (HISTO-MRS) PDFF data were obtained. By temporal splitting, the total population was divided into development and validation sets. Receiver operating characteristic (ROC) analysis was performed to evaluate the diagnostic performance of the MRI-PDFF method. Two cutoff values with sensitivity > 90% and specificity > 90% were selected to rule-out and rule-in, respectively, hepatic steatosis with reference to HFF ≥ 5% in the development set. The diagnostic performance was assessed using the validation set. RESULTS Of 921 final participants (624 male; mean age ± standard deviation, 31.5 ± 9.0 years), the development and validation sets comprised 497 and 424 patients, respectively. In the development set, the areas under the ROC curve for diagnosing hepatic steatosis were 0.920 for CS-MRI-PDFF and 0.915 for HISTO-MRS-PDFF. For ruling-out hepatic steatosis, the CS-MRI-PDFF cutoff was 2.3% (sensitivity, 92.4%; specificity, 63.0%) and the HISTO-MRI-PDFF cutoff was 2.6% (sensitivity, 88.8%; specificity, 70.1%). For ruling-in hepatic steatosis, the CS-MRI-PDFF cutoff was 3.5% (sensitivity, 73.5%; specificity, 88.6%) and the HISTO-MRI-PDFF cutoff was 4.0% (sensitivity, 74.7%; specificity, 90.6%). CONCLUSION In a large population of healthy adults, our study suggests diagnostic thresholds for ruling-out and ruling-in hepatic steatosis defined as HFF ≥ 5% by contemporary PDFF measurement methods.
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Affiliation(s)
- Sohee Park
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Jae Hyun Kwon
- Department of Surgery, Hallym University Sacred Heart Hospital, Anyang, Korea
| | - So Yeon Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Ji Hun Kang
- Department of Radiology, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri, Korea
| | - Jung Il Chung
- University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Jong Keon Jang
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Hye Young Jang
- Department of Radiology, National Cancer Center, Goyang, Korea
| | - Ju Hyun Shim
- Department of Gastroenterology, Asan Liver Center, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Seung Soo Lee
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Kyoung Won Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Gi-Won Song
- Department of Surgery, Division of Hepatobiliary and Liver Transplantation Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
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Retrospective comparison of liver chemical shift-encoded PDFF sampling strategies in children and adolescents. ABDOMINAL RADIOLOGY (NEW YORK) 2022; 47:3478-3484. [PMID: 35864263 DOI: 10.1007/s00261-022-03615-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 07/01/2022] [Accepted: 07/05/2022] [Indexed: 01/18/2023]
Abstract
INTRODUCTION Multiple region-of-interest (ROI) sampling strategies have been described for liver fat quantification by MRI PDFF. While adult studies have shown that sampling strategies including as few as four ROIs provide a reasonable tradeoff between laboriousness and quantitative performance, there is a paucity of similar data for pediatric patients. PURPOSE To assess agreement between different ROI sampling strategies for liver MRI PDFF analysis in children and adolescents. MATERIALS AND METHODS This retrospective, internal review board-approved study included clinical MRI PDFF acquisitions for 50 children and adolescents. Four different ROI sampling paradigms reported in the literature were reproduced to measure mean liver PDFF. An 18-ROI (2 in each Couinaud segment) paradigm was considered the reference standard. Spearman correlation, intraclass correlation coefficients (ICCs), and Bland-Altman analyses were used to quantify agreement. RESULTS Mean age for the 50 participants was 14 ± 2.5 years (range 8-17 years). Based on the 18-ROI paradigm, mean PDFF was significantly higher for the right lobe (24.0 ± 13.7% right, 22.0 ± 13.1% left; p = 0.001). PDFF values for each individual Couinaud segment were highly correlated with the reference standard (ρ = 0.977 to 0.993, p < 0.0001). PDFF values derived from all sampling paradigms, including strategies using large free-hand ROIs, were strongly correlated with the reference standard (ρ = 0.995 to 0.998, p < 0.0001) with excellent agreement (ICC range 0.995 to 0.998). CONCLUSION Liver PDFF sampling paradigms using large ROIs showed strong correlation, excellent agreement, and nonsignificant mean differences from a reference standard paradigm sampling every Couinaud segment in children. Paradigms that exclusively sample the right lobe may overestimate liver PDFF.
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27
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Li YW, Jiao Y, Chen N, Gao Q, Chen YK, Zhang YF, Wen QP, Zhang ZM. How to select the quantitative magnetic resonance technique for subjects with fatty liver: A systematic review. World J Clin Cases 2022; 10:8906-8921. [PMID: 36157636 PMCID: PMC9477046 DOI: 10.12998/wjcc.v10.i25.8906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Revised: 05/25/2022] [Accepted: 07/22/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Early quantitative assessment of liver fat content is essential for patients with fatty liver disease. Mounting evidence has shown that magnetic resonance (MR) technique has high accuracy in the quantitative analysis of fatty liver, and is suitable for monitoring the therapeutic effect on fatty liver. However, many packaging methods and postprocessing functions have puzzled radiologists in clinical applications. Therefore, selecting a quantitative MR imaging technique for patients with fatty liver disease remains challenging.
AIM To provide information for the proper selection of commonly used quantitative MR techniques to quantify fatty liver.
METHODS We completed a systematic literature review of quantitative MR techniques for detecting fatty liver, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol. Studies were retrieved from PubMed, Embase, and Cochrane Library databases, and their quality was assessed using the Quality Assessment of Diagnostic Studies criteria. The Reference Citation Analysis database (https://www.referencecitationanalysis.com) was used to analyze citation of articles which were included in this review.
RESULTS Forty studies were included for spectroscopy, two-point Dixon imaging, and multiple-point Dixon imaging comparing liver biopsy to other imaging methods. The advantages and disadvantages of each of the three techniques and their clinical diagnostic performances were analyzed.
CONCLUSION The proton density fat fraction derived from multiple-point Dixon imaging is a noninvasive method for accurate quantitative measurement of hepatic fat content in the diagnosis and monitoring of fatty liver progression.
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Affiliation(s)
- You-Wei Li
- Department of Radiology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing 100144, China
| | - Yang Jiao
- Department of Rehabilitation Psychology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing 100144, China
| | - Na Chen
- Department of Otorhinolaryngology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing 100144, China
| | - Qiang Gao
- Department of Gastroenterology and Hepatology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing 100144, China
| | - Yu-Kun Chen
- Department of Radiology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing 100144, China
| | - Yuan-Fang Zhang
- Department of Radiology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing 100144, China
| | - Qi-Ping Wen
- Department of Radiology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing 100144, China
| | - Zong-Ming Zhang
- Department of General Surgery, Beijing Electric Power Hospital, State Grid Corporation of China, Capital Medical University, Beijing 100073, China
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28
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Welle CL, Olson MC, Reeder SB, Venkatesh SK. Magnetic Resonance Imaging of Liver Fibrosis, Fat, and Iron. Radiol Clin North Am 2022; 60:705-716. [PMID: 35989039 DOI: 10.1016/j.rcl.2022.04.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Li S, Shen C, Ding Z, She H, Du YP. Accelerating multi-echo chemical shift encoded water-fat MRI using model-guided deep learning. Magn Reson Med 2022; 88:1851-1866. [PMID: 35649172 DOI: 10.1002/mrm.29307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 04/30/2022] [Accepted: 05/02/2022] [Indexed: 11/10/2022]
Abstract
PURPOSE To accelerate chemical shift encoded (CSE) water-fat imaging by applying a model-guided deep learning water-fat separation (MGDL-WF) framework to the undersampled k-space data. METHODS A model-guided deep learning water-fat separation framework is proposed for the acceleration using Cartesian/radial undersampling data. The proposed MGDL-WF combines the power of CSE water-fat imaging model and data-driven deep learning by jointly using a multi-peak fat model and a modified residual U-net network. The model is used to guide the image reconstruction, and the network is used to capture the artifacts induced by the undersampling. A data consistency layer is used in MGDL-WF to ensure the output images to be consistent with the k-space measurements. A Gauss-Newton iteration algorithm is adapted for the gradient updating of the networks. RESULTS Compared with the compressed sensing water-fat separation (CS-WF) algorithm/2-step procedure algorithm, the MGDL-WF increased peak signal-to-noise ratio (PSNR) by 5.31/5.23, 6.11/4.54, and 4.75 dB/1.88 dB with Cartesian sampling, and by 4.13/6.53, 2.90/4.68, and 1.68 dB/3.48 dB with radial sampling, at acceleration rates (R) of 4, 6, and 8, respectively. By using MGDL-WF, radial sampling increased the PSNR by 2.07 dB at R = 8, compared with Cartesian sampling. CONCLUSIONS The proposed MGDL-WF enables exploiting features of the water images and fat images from the undersampled multi-echo data, leading to improved performance in the accelerated CSE water-fat imaging. By using MGDL-WF, radial sampling can further improve the image quality with comparable scan time in comparison with Cartesian sampling.
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Affiliation(s)
- Shuo Li
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Chenfei Shen
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Zekang Ding
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Huajun She
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Yiping P Du
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
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Lortie J, Rush B, Osterbauer K, Colgan TJ, Tamada D, Garlapati S, Campbell TC, Traynor A, Leal T, Patel V, Helgager JJ, Lee K, Reeder SB, Kuchnia AJ. Myosteatosis as a Shared Biomarker for Sarcopenia and Cachexia Using MRI and Ultrasound. FRONTIERS IN REHABILITATION SCIENCES 2022; 3:896114. [PMID: 36189019 PMCID: PMC9397668 DOI: 10.3389/fresc.2022.896114] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 04/25/2022] [Indexed: 12/03/2022]
Abstract
Purpose Establish bedside biomarkers of myosteatosis for sarcopenia and cachexia. We compared ultrasound biomarkers against MRI-based percent fat, histology, and CT-based muscle density among healthy adults and adults undergoing treatment for lung cancer. Methods We compared ultrasound and MRI myosteatosis measures among young healthy, older healthy, and older adults with non-small cell lung cancer undergoing systemic treatment, all without significant medical concerns, in a cross-sectional pilot study. We assessed each participant's rectus femoris ultrasound-based echo intensity (EI), shear wave elastography-based shear wave speed, and MRI-based proton density fat-fraction (PDFF). We also assessed BMI, rectus femoris thickness and cross-sectional area. Rectus femoris biopsies were taken for all older adults (n = 20) and we analyzed chest CT scans for older adults undergoing treatment (n = 10). We determined associations between muscle assessments and BMI, and compared these assessments between groups. Results A total of 10 young healthy adults, 10 older healthy adults, and 10 older adults undergoing treatment were recruited. PDFF was lower in young adults than in older healthy adults and older adults undergoing treatment (0.3 vs. 2.8 vs. 2.9%, respectively, p = 0.01). Young adults had significantly lower EI than older healthy adults, but not older adults undergoing treatment (48.6 vs. 81.8 vs. 75.4, p = 0.02). When comparing associations between measures, PDFF was strongly associated with EI (ρ = 0.75, p < 0.01) and moderately negatively associated with shear wave speed (ρ = −0.49, p < 0.01) but not BMI, whole leg cross-sectional area, or rectus femoris cross-sectional area. Among participants with CT scans, paraspinal muscle density was significantly associated with PDFF (ρ = −0.70, p = 0.023). Histological markers of inflammation or degradation did not differ between older adult groups. Conclusion PDFF was sensitive to myosteatosis between young adults and both older adult groups. EI was less sensitive to myosteatosis between groups, yet EI was strongly associated with PDFF unlike BMI, which is typically used in cachexia diagnosis. Our results suggest that ultrasound measures may serve to determine myosteatosis at the bedside and are more useful diagnostically than traditional weight assessments like BMI. These results show promise of using EI, shear wave speed, and PDFF proxies of myosteatosis as diagnostic and therapeutic biomarkers of sarcopenia and cachexia.
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Affiliation(s)
- Jevin Lortie
- Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, WI, United States
- *Correspondence: Jevin Lortie
| | - Benjamin Rush
- Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, WI, United States
| | - Katie Osterbauer
- Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, WI, United States
| | - T. J. Colgan
- Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, United States
| | - Daiki Tamada
- Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, United States
| | - Sujay Garlapati
- Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, WI, United States
| | - Toby C. Campbell
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, United States
| | - Anne Traynor
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, United States
| | - Ticiana Leal
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, United States
- Department of Hematology and Medical Oncology, Emory University School of Medicine, Atlanta, GA, United States
| | - Viharkumar Patel
- Department of Pathology, Harvard Medical School, Boston, MA, United States
| | - Jeffrey J. Helgager
- Department of Pathology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, United States
| | - Kenneth Lee
- Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, United States
| | - Scott B. Reeder
- Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, United States
| | - Adam J. Kuchnia
- Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, WI, United States
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Wang X, Tan Y, Liu D, Shen H, Deng Y, Tan Y, Wang L, Zhang Y, Ma X, Zeng X, Zhang J. Chemotherapy-associated steatohepatitis was concomitant with epicardial adipose tissue volume increasing in breast cancer patients who received neoadjuvant chemotherapy. Eur Radiol 2022; 32:4898-4908. [PMID: 35394181 DOI: 10.1007/s00330-022-08581-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 01/08/2022] [Accepted: 01/12/2022] [Indexed: 12/16/2022]
Abstract
OBJECTIVES To investigate the prevalence of chemotherapy-associated steatohepatitis, quantitate the epicardial adipose tissue (EAT) volume in breast cancer patients, and explore the mediating effect of liver fat content on EAT volume in breast cancer patients who received neoadjuvant chemotherapy (NAC). METHODS From October 2018 to April 2020, patients were retrospectively reviewed and divided into breast cancer non-NAC and NAC groups. The prevalence of chemotherapy-associated steatohepatitis was evaluated through quantitative MRI mDIXON-Quant examinations by using defined proton density fat fraction cutoffs of liver fat. The EAT volume was quantified on chest CT by semi-automatic volume analysis software. Bootstrap analysis was used in the breast cancer NAC group to test the significance of the mediating effect of liver fat content on EAT volume. RESULTS A total of 662 breast cancer patients (non-NAC group: 445 patients; NAC group: 217 patients) were included. The prevalence of chemotherapy-associated steatohepatitis in the NAC group was significantly higher than the prevalence of hepatic steatosis in the non-NAC group (42.8% vs. 33.3%, p < 0.001). EAT volume was measured in 561 of 662 breast cancer patients, and was significantly higher in the NAC group than in the non-NAC group (137.26 ± 53.48 mL vs. 125.14 ± 58.77 mL, p = 0.020). In the breast cancer NAC group, the indirect effect of liver fat content on EAT volume was 2.545 (p < 0.001), and the contribution rate to the effect was 69.1%. CONCLUSIONS EAT volume was significantly higher in the BC-NAC group than in the BC-non-NAC group. KEY POINTS • The prevalence of CASH was as high as 42.8% in BC patients. • NAC significantly increased the EAT volume in BC patients. • The liver fat content caused the change of EAT volume through mediating effect.
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Affiliation(s)
- Xiaoxia Wang
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, No.181 Hanyu Road, Shapingba District, Chongqing, 400030, People's Republic of China
| | - Yuchuan Tan
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, No.181 Hanyu Road, Shapingba District, Chongqing, 400030, People's Republic of China
| | - Daihong Liu
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, No.181 Hanyu Road, Shapingba District, Chongqing, 400030, People's Republic of China
| | - Hesong Shen
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, No.181 Hanyu Road, Shapingba District, Chongqing, 400030, People's Republic of China
| | - Yongchun Deng
- Department of Breast Cancer Center, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, 400030, People's Republic of China
| | - Yong Tan
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, No.181 Hanyu Road, Shapingba District, Chongqing, 400030, People's Republic of China
| | - Lei Wang
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, No.181 Hanyu Road, Shapingba District, Chongqing, 400030, People's Republic of China
| | - Yipeng Zhang
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, No.181 Hanyu Road, Shapingba District, Chongqing, 400030, People's Republic of China
| | - Xin Ma
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, No.181 Hanyu Road, Shapingba District, Chongqing, 400030, People's Republic of China
| | - Xiaohua Zeng
- Department of Breast Cancer Center, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, 400030, People's Republic of China.
| | - Jiuquan Zhang
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, No.181 Hanyu Road, Shapingba District, Chongqing, 400030, People's Republic of China.
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Brancato V, Della Pepa G, Bozzetto L, Vitale M, Annuzzi G, Basso L, Cavaliere C, Salvatore M, Rivellese AA, Monti S. Evaluation of a Whole-Liver Dixon-Based MRI Approach for Quantification of Liver Fat in Patients with Type 2 Diabetes Treated with Two Isocaloric Different Diets. Diagnostics (Basel) 2022; 12:diagnostics12020514. [PMID: 35204604 PMCID: PMC8871286 DOI: 10.3390/diagnostics12020514] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 02/04/2022] [Accepted: 02/15/2022] [Indexed: 02/04/2023] Open
Abstract
Dixon-based methods for the detection of fatty liver have the advantage of being non-invasive, easy to perform and analyze, and to provide a whole-liver coverage during the acquisition. The aim of the study was to assess the feasibility of a whole-liver Dixon-based approach for liver fat quantification in type 2 diabetes (T2D) patients who underwent two different isocaloric dietary treatments: a diet rich in monosaturated fatty acids (MUFA) and a multifactorial diet. Thirty-nine T2D patients were randomly assigned to MUFA diet (n = 21) and multifactorial diet (n = 18). The mean values of the proton density fat fraction (PDFF) over the whole liver and over the ROI corresponding to that chosen for MRS were compared to MRS-PDFF using Spearman’s correlation (ρ). Before–after changes in percentage of liver volume corresponding to MRI-PDFF above thresholds associated with hepatic steatosis (LV%TH, with TH = 5.56%, 7.97% and 8.8%) were considered to assess the proposed approach and compared between diets using Wilcoxon rank-sum test. Statistical significance set at p < 0.05. A strong linear relationship was found between MRS-PDFF and MRI-PDFFs (ρ = 0.85, p < 0.0001). Changes in LV%TH% were significantly higher (p < 0.05) in the multifactorial diet than in MUFA diet (25% vs. 9%, 35% vs. 12%, and 38% vs. 13% decrease, respectively, for TH = 5.56%, 7.97%, and 8.8%) and this was reproducible compared to results obtained using the standard liver fat analysis. A volumetric approach based on Dixon method could be an effective, non-invasive technique that could be used for the quantitative analysis of hepatic steatosis in T2D patients.
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Affiliation(s)
- Valentina Brancato
- IRCCS Synlab SDN, 80143 Naples, Italy; (L.B.); (C.C.); (M.S.)
- Correspondence:
| | - Giuseppe Della Pepa
- Department of Clinical Medicine and Surgery, University of Naples Federico II, 80131 Naples, Italy; (G.D.P.); (L.B.); (M.V.); (G.A.); (A.A.R.)
| | - Lutgarda Bozzetto
- Department of Clinical Medicine and Surgery, University of Naples Federico II, 80131 Naples, Italy; (G.D.P.); (L.B.); (M.V.); (G.A.); (A.A.R.)
| | - Marilena Vitale
- Department of Clinical Medicine and Surgery, University of Naples Federico II, 80131 Naples, Italy; (G.D.P.); (L.B.); (M.V.); (G.A.); (A.A.R.)
| | - Giovanni Annuzzi
- Department of Clinical Medicine and Surgery, University of Naples Federico II, 80131 Naples, Italy; (G.D.P.); (L.B.); (M.V.); (G.A.); (A.A.R.)
| | - Luca Basso
- IRCCS Synlab SDN, 80143 Naples, Italy; (L.B.); (C.C.); (M.S.)
| | - Carlo Cavaliere
- IRCCS Synlab SDN, 80143 Naples, Italy; (L.B.); (C.C.); (M.S.)
| | - Marco Salvatore
- IRCCS Synlab SDN, 80143 Naples, Italy; (L.B.); (C.C.); (M.S.)
| | - Angela Albarosa Rivellese
- Department of Clinical Medicine and Surgery, University of Naples Federico II, 80131 Naples, Italy; (G.D.P.); (L.B.); (M.V.); (G.A.); (A.A.R.)
| | - Serena Monti
- Institute of Biostructures and Bioimaging, National Research Council, 80145 Naples, Italy;
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Fortier V, Levesque IR. Longitudinal relaxation in fat-water mixtures and its dependence on fat content at 3 T. NMR IN BIOMEDICINE 2022; 35:e4629. [PMID: 34636097 DOI: 10.1002/nbm.4629] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 08/27/2021] [Accepted: 09/14/2021] [Indexed: 06/13/2023]
Abstract
Longitudinal (T1 ) relaxation of triglyceride molecules and water is of interest for fat-water separation and fat quantification. A better understanding of T1 relaxation could benefit modeling for applications in fat quantification and relaxation mapping. This work investigated T1 relaxation of spectral resonances of triglyceride molecules and water in liquid fat-water mixtures and its dependence on the fat fraction. Dairy cream and a safflower oil emulsion were used. These were diluted with distilled water to produce a variety of fat mass fractions (4.4% to 35% in dairy cream and 6.3% to 52.3% in safflower oil emulsion). T1 was measured at room temperature at 3 T using an inversion recovery STimulated Echo Acquisition Mode (STEAM) MR spectroscopy method with a series of inversion times. T1 variations as a function of fat fraction were investigated for various resonances. A two-component model was developed to describe the relaxation in a fat-water mixture as a function of the fat fraction. The T1 of water and of all fat resonances studied in this work decreased as the fat fraction increased. The relative variation in T1 was different for each fat resonance. The T1 of the methylene resonance showed the least variation as a function of the fat fraction. The proposed two-component model closely fits the observed T1 variations. In conclusion, this work clarifies how the T1 of major and minor fat resonances and of the water resonance varies as a function of the fat fraction in fat-water mixtures. Knowledge of these variations could serve modeling, analysis of MRI measurements in fat-water mixtures, and phantom preparation.
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Affiliation(s)
- Véronique Fortier
- Medical Physics Unit, McGill University, Montréal, QC, Canada
- Biomedical Engineering, McGill University, Montréal, QC, Canada
| | - Ives R Levesque
- Medical Physics Unit, McGill University, Montréal, QC, Canada
- Biomedical Engineering, McGill University, Montréal, QC, Canada
- Research Institute of the McGill University Health Centre, Montréal, QC, Canada
- Gerald Bronfman Department of Oncology, McGill University, Montréal, Canada
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Wagner R, Eckstein SS, Yamazaki H, Gerst F, Machann J, Jaghutriz BA, Schürmann A, Solimena M, Singer S, Königsrainer A, Birkenfeld AL, Häring HU, Fritsche A, Ullrich S, Heni M. Metabolic implications of pancreatic fat accumulation. Nat Rev Endocrinol 2022; 18:43-54. [PMID: 34671102 DOI: 10.1038/s41574-021-00573-3] [Citation(s) in RCA: 74] [Impact Index Per Article: 24.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/13/2021] [Indexed: 12/15/2022]
Abstract
Fat accumulation outside subcutaneous adipose tissue often has unfavourable effects on systemic metabolism. In addition to non-alcoholic fatty liver disease, which has received considerable attention, pancreatic fat has become an important area of research throughout the past 10 years. While a number of diagnostic approaches are available to quantify pancreatic fat, multi-echo Dixon MRI is currently the most developed method. Initial studies have shown associations between pancreatic fat and the metabolic syndrome, impaired glucose metabolism and type 2 diabetes mellitus. Pancreatic fat is linked to reduced insulin secretion, at least under specific circumstances such as prediabetes, low BMI and increased genetic risk of type 2 diabetes mellitus. This Review summarizes the possible causes and metabolic consequences of pancreatic fat accumulation. In addition, potential therapeutic approaches for addressing pancreatic fat accumulation are discussed.
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Affiliation(s)
- Robert Wagner
- Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tübingen, Tübingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
- Department of Internal Medicine, Division of Diabetology, Endocrinology, and Nephrology, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Sabine S Eckstein
- Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tübingen, Tübingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
| | - Hajime Yamazaki
- Section of Clinical Epidemiology, Department of Community Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Felicia Gerst
- Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tübingen, Tübingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
- Department of Internal Medicine, Division of Diabetology, Endocrinology, and Nephrology, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Jürgen Machann
- Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tübingen, Tübingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
- Section of Experimental Radiology, Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Benjamin Assad Jaghutriz
- Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tübingen, Tübingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
- Department of Internal Medicine, Division of Diabetology, Endocrinology, and Nephrology, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Annette Schürmann
- German Center for Diabetes Research (DZD), Tübingen, Germany
- Department of Experimental Diabetology, German Institute of Human Nutrition (DIfE), Potsdam-Rehbrücke, Germany
- Institute of Nutritional Science, University of Potsdam, Potsdam, Germany
| | - Michele Solimena
- German Center for Diabetes Research (DZD), Tübingen, Germany
- Molecular Diabetology, University Hospital and Faculty of Medicine Carl Gustav Carus, TU Dresden, Dresden, Germany
- Paul Langerhans Institute Dresden (PLID), Helmholtz Center Munich, University Hospital and Faculty of Medicine Carl Gustav Carus, TU Dresden, Dresden, Germany
| | - Stephan Singer
- Institute of Pathology, University of Tübingen, Tübingen, Germany
| | - Alfred Königsrainer
- Department of General, Visceral, and Transplant Surgery, University Hospital Tübingen, Tübingen, Germany
| | - Andreas L Birkenfeld
- Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tübingen, Tübingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
- Department of Internal Medicine, Division of Diabetology, Endocrinology, and Nephrology, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Hans-Ulrich Häring
- Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tübingen, Tübingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
- Department of Internal Medicine, Division of Diabetology, Endocrinology, and Nephrology, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Andreas Fritsche
- Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tübingen, Tübingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
- Department of Internal Medicine, Division of Diabetology, Endocrinology, and Nephrology, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Susanne Ullrich
- Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tübingen, Tübingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
- Department of Internal Medicine, Division of Diabetology, Endocrinology, and Nephrology, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Martin Heni
- Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tübingen, Tübingen, Germany.
- German Center for Diabetes Research (DZD), Tübingen, Germany.
- Department of Internal Medicine, Division of Diabetology, Endocrinology, and Nephrology, Eberhard Karls University Tübingen, Tübingen, Germany.
- Institute for Clinical Chemistry and Pathobiochemistry, Department for Diagnostic Laboratory Medicine, University Hospital Tübingen, Tübingen, Germany.
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Weingärtner S, Desmond KL, Obuchowski NA, Baessler B, Zhang Y, Biondetti E, Ma D, Golay X, Boss MA, Gunter JL, Keenan KE, Hernando D. Development, validation, qualification, and dissemination of quantitative MR methods: Overview and recommendations by the ISMRM quantitative MR study group. Magn Reson Med 2021; 87:1184-1206. [PMID: 34825741 DOI: 10.1002/mrm.29084] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 10/20/2021] [Accepted: 10/27/2021] [Indexed: 12/26/2022]
Abstract
On behalf of the International Society for Magnetic Resonance in Medicine (ISMRM) Quantitative MR Study Group, this article provides an overview of considerations for the development, validation, qualification, and dissemination of quantitative MR (qMR) methods. This process is framed in terms of two central technical performance properties, i.e., bias and precision. Although qMR is confounded by undesired effects, methods with low bias and high precision can be iteratively developed and validated. For illustration, two distinct qMR methods are discussed throughout the manuscript: quantification of liver proton-density fat fraction, and cardiac T1 . These examples demonstrate the expansion of qMR methods from research centers toward widespread clinical dissemination. The overall goal of this article is to provide trainees, researchers, and clinicians with essential guidelines for the development and validation of qMR methods, as well as an understanding of necessary steps and potential pitfalls for the dissemination of quantitative MR in research and in the clinic.
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Affiliation(s)
- Sebastian Weingärtner
- Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands
| | - Kimberly L Desmond
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Nancy A Obuchowski
- Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio, USA
| | - Bettina Baessler
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland
| | - Yuxin Zhang
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Emma Biondetti
- Department of Neuroscience, Imaging and Clinical Sciences, D'Annunzio University of Chieti and Pescara, Chieti, Italy
| | - Dan Ma
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Xavier Golay
- Brain Repair & Rehabilitation, Institute of Neurology, University College London, United Kingdom.,Gold Standard Phantoms Limited, Rochester, United Kingdom
| | - Michael A Boss
- Center for Research and Innovation, American College of Radiology, Philadelphia, Pennsylvania, USA
| | | | - Kathryn E Keenan
- National Institute of Standards and Technology, Boulder, Colorado, USA
| | - Diego Hernando
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
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[Value of a nomogram model based on IDEAL-IQ for predicting early bone mass loss]. NAN FANG YI KE DA XUE XUE BAO = JOURNAL OF SOUTHERN MEDICAL UNIVERSITY 2021; 41:1707-1711. [PMID: 34916198 PMCID: PMC8685713 DOI: 10.12122/j.issn.1673-4254.2021.11.16] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
OBJECTIVE To assess the diagnostic efficiency of a nomogram model based on iterative decomposition of water and fat with echo asymmetry and least-squares estimation- iron quantification (IDEAL- IQ) for predicting early bone loss of the lumbar vertebrae. METHODS Fifty-nine volunteers and patients with osteoporosis underwent examinations with both dual-energy X-ray absorptiometry (DXA) to determine bone mineral density (BMD) of L1-4 vertebrae and lumbar magnetic resonance imaging (MRI) with IDEAL-IQ sequence for measurement of bone marrow FF of L1-4 vertebrae. According to the results of DXA, the subjects were divided into normal bone mass group (n=23) and osteopenia group (n=36). The FF values of the two groups were compared and the diagnostic efficacy of the FF value was evaluated using ROC curve analysis. Multivariate logistic regression analysis was used to identify the independent factors for predicting bone mass loss, and a visual nomogram model was constructed and its diagnostic efficiency was assessed. RESULTS The FF value of the vertebrae was significant lower in normal bone mass group than in osteopenia group [(38.84±6.75)% vs (51.96±7.65)%, P < 0.05). ROC curve analysis showed that the AUC of the FF value for differentiating normal bone mass and osteopenia was 0.797 with a cutoff value of 46.85%, a sensitivity of 73.91% and a specificity of 80.56%. Multivariate logistics regression analysis identified the FF value, age and BMI as the independent factors for predicting bone mass loss. The diagnostic AUC of the nomogram model was 0.954 (95% CI: 0.806-0.957), and the predicted probability of the model was in good agreement with the actual probability. Decision curve analysis showed that the nomogram model could provide more net benefit than the FF vale alone. CONCLUSION FF value of MRI IDEAL- IQ sequence can reflect bone marrow fat content of the vertebral body, and the nomogram model incorporating the FF value, age, and BMI can further improve the predictive efficiency to provide a visual modality for predicting early bone mass loss.
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37
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Velasco C, Cruz G, Jaubert O, Lavin B, Botnar RM, Prieto C. Simultaneous comprehensive liver T 1 , T 2 , T 2 ∗ , T 1ρ , and fat fraction characterization with MR fingerprinting. Magn Reson Med 2021; 87:1980-1991. [PMID: 34792212 DOI: 10.1002/mrm.29089] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 10/18/2021] [Accepted: 10/29/2021] [Indexed: 12/23/2022]
Abstract
PURPOSE To develop a novel simultaneous co-registered T1 , T2 , T 2 ∗ , T1ρ , and fat fraction abdominal MR fingerprinting (MRF) approach for fully comprehensive liver-tissue characterization in a single breath-hold scan. METHODS A gradient-echo liver MRF sequence with low fixed flip angle, multi-echo radial readout, and varying magnetization preparation pulses for multiparametric encoding is performed at 1.5 T. The T 2 ∗ and fat fraction are estimated from a graph/cut water/fat separation method using a six-peak fat model. Water/fat singular images obtained are then matched to an MRF dictionary, estimating water-specific T1 , T2 , and T1ρ . The proposed approach was tested in phantoms and 10 healthy subjects and compared against conventional sequences. RESULTS For the phantom studies, linear fits show excellent coefficients of determination (r2 > 0.9) for every parametric map. For in vivo studies, the average values measured within regions of interest drawn on liver, spleen, muscle, and fat are statistically different from the reference scans (p < 0.05) for T1 , T2 , and T1⍴ but not for T 2 ∗ and fat fraction, whereas correlation between MRF and reference scans is excellent for each parameter (r2 > 0.92 for every parameter). CONCLUSION The proposed multi-echo inversion-recovery, T2 , and T1⍴ prepared liver MRF sequence presented in this work allows for quantitative T1 , T2 , T 2 ∗ , T1⍴ , and fat fraction liver-tissue characterization in a single breath-hold scan of 18 seconds. The approach showed good agreement and correlation with respect to reference clinical maps.
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Affiliation(s)
- Carlos Velasco
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Gastão Cruz
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Olivier Jaubert
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Begoña Lavin
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.,Department of Biochemistry and Molecular Biology, School of Chemistry, Complutense University of Madrid, Madrid, Spain
| | - René M Botnar
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.,School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.,School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
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38
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Chan HJ, Zhou Z, Fang J, Tai DI, Tseng JH, Lai MW, Hsieh BY, Yamaguchi T, Tsui PH. Ultrasound Sample Entropy Imaging: A New Approach for Evaluating Hepatic Steatosis and Fibrosis. IEEE JOURNAL OF TRANSLATIONAL ENGINEERING IN HEALTH AND MEDICINE 2021; 9:1800612. [PMID: 34786215 PMCID: PMC8580366 DOI: 10.1109/jtehm.2021.3124937] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Revised: 08/20/2021] [Accepted: 10/10/2021] [Indexed: 02/05/2023]
Abstract
Objective: Hepatic steatosis causes nonalcoholic fatty liver disease and may progress to fibrosis. Ultrasound is the first-line approach to examining hepatic steatosis. Fatty droplets in the liver parenchyma alter ultrasound radiofrequency (RF) signal statistical properties. This study proposes using sample entropy, a measure of irregularity in time-series data determined by the dimension [Formula: see text] and tolerance [Formula: see text], for ultrasound parametric imaging of hepatic steatosis and fibrosis. Methods: Liver donors and patients were enrolled, and their hepatic fat fraction (HFF) ([Formula: see text]), steatosis grade ([Formula: see text]), and fibrosis score ([Formula: see text]) were measured to verify the results of sample entropy imaging using sliding-window processing of ultrasound RF data. Results: The sample entropy calculated using [Formula: see text] 4 and [Formula: see text] was highly correlated with the HFF when a small window with a side length of one pulse was used. The areas under the receiver operating characteristic curve for detecting hepatic steatosis that was [Formula: see text]mild, [Formula: see text]moderate, and [Formula: see text]severe were 0.86, 0.90, and 0.88, respectively, and the area was 0.87 for detecting liver fibrosis in individuals with significant steatosis. Discussion/Conclusions: Ultrasound sample entropy imaging enables the identification of time-series patterns in RF signals received from the liver. The algorithmic scheme proposed in this study is compatible with general ultrasound pulse-echo systems, allowing clinical fibrosis risk evaluations of individuals with developing hepatic steatosis.
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Affiliation(s)
- Hsien-Jung Chan
- Department of Medical Imaging and Radiological SciencesCollege of Medicine, Chang Gung UniversityTaoyuan333323Taiwan
| | - Zhuhuang Zhou
- Department of Biomedical EngineeringFaculty of Environment and LifeBeijing University of TechnologyBeijing100124China
| | - Jui Fang
- X-Dimension Center for Medical Research and TranslationChina Medical University HospitalTaichung40447Taiwan
| | - Dar-In Tai
- Department of Gastroenterology and HepatologyChang Gung Memorial Hospital at LinkouTaoyuan333423Taiwan
| | - Jeng-Hwei Tseng
- Department of Medical Imaging and InterventionChang Gung Memorial Hospital at LinkouTaoyuan333423Taiwan
| | - Ming-Wei Lai
- Division of Pediatric GastroenterologyDepartment of PediatricsChang Gung Memorial Hospital at LinkouTaoyuan333423Taiwan
| | - Bao-Yu Hsieh
- Department of Medical Imaging and Radiological SciencesCollege of Medicine, Chang Gung UniversityTaoyuan333323Taiwan
- Department of Medical Imaging and InterventionChang Gung Memorial Hospital at LinkouTaoyuan333423Taiwan
| | - Tadashi Yamaguchi
- Center for Frontier Medical EngineeringChiba UniversityChiba263-8522Japan
| | - Po-Hsiang Tsui
- Department of Medical Imaging and Radiological SciencesCollege of Medicine, Chang Gung UniversityTaoyuan333323Taiwan
- Division of Pediatric GastroenterologyDepartment of PediatricsChang Gung Memorial Hospital at LinkouTaoyuan333423Taiwan
- Institute for Radiological Research, Chang Gung UniversityTaoyuan333323Taiwan
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Starekova J, Hernando D, Pickhardt PJ, Reeder SB. Quantification of Liver Fat Content with CT and MRI: State of the Art. Radiology 2021; 301:250-262. [PMID: 34546125 PMCID: PMC8574059 DOI: 10.1148/radiol.2021204288] [Citation(s) in RCA: 123] [Impact Index Per Article: 30.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 04/19/2021] [Accepted: 04/26/2021] [Indexed: 12/13/2022]
Abstract
Hepatic steatosis is defined as pathologically elevated liver fat content and has many underlying causes. Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease worldwide, with an increasing prevalence among adults and children. Abnormal liver fat accumulation has serious consequences, including cirrhosis, liver failure, and hepatocellular carcinoma. In addition, hepatic steatosis is increasingly recognized as an independent risk factor for the metabolic syndrome, type 2 diabetes, and, most important, cardiovascular mortality. During the past 2 decades, noninvasive imaging-based methods for the evaluation of hepatic steatosis have been developed and disseminated. Chemical shift-encoded MRI is now established as the most accurate and precise method for liver fat quantification. CT is important for the detection and quantification of incidental steatosis and may play an increasingly prominent role in risk stratification, particularly with the emergence of CT-based screening and artificial intelligence. Quantitative imaging methods are increasingly used for diagnostic work-up and management of steatosis, including treatment monitoring. The purpose of this state-of-the-art review is to provide an overview of recent progress and current state of the art for liver fat quantification using CT and MRI, as well as important practical considerations related to clinical implementation.
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Affiliation(s)
- Jitka Starekova
- From the Departments of Radiology (J.S., D.H., P.J.P., S.B.R.),
Medical Physics (D.H., S.B.R.), Biomedical Engineering (S.B.R.), Medicine
(S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, 1111
Highland Ave, Madison, WI 53705
| | - Diego Hernando
- From the Departments of Radiology (J.S., D.H., P.J.P., S.B.R.),
Medical Physics (D.H., S.B.R.), Biomedical Engineering (S.B.R.), Medicine
(S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, 1111
Highland Ave, Madison, WI 53705
| | - Perry J. Pickhardt
- From the Departments of Radiology (J.S., D.H., P.J.P., S.B.R.),
Medical Physics (D.H., S.B.R.), Biomedical Engineering (S.B.R.), Medicine
(S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, 1111
Highland Ave, Madison, WI 53705
| | - Scott B. Reeder
- From the Departments of Radiology (J.S., D.H., P.J.P., S.B.R.),
Medical Physics (D.H., S.B.R.), Biomedical Engineering (S.B.R.), Medicine
(S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, 1111
Highland Ave, Madison, WI 53705
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Ballard DH, Ludwig DR, Fraum TJ, Salter A, Narra VR, Shetty AS. Quality Control of Magnetic Resonance Elastography Using Percent Measurable Liver Volume Estimation. J Magn Reson Imaging 2021; 55:1890-1899. [PMID: 34704644 DOI: 10.1002/jmri.27976] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 10/17/2021] [Accepted: 10/19/2021] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Although studies have described factors associated with failed magnetic resonance elastography (MRE), little is known about what factors influence usable elastography data. PURPOSE To identify factors that have a negative impact on percent measurable liver volume (pMLV), defined as the proportion of usable liver elastography data relative to the volume of imaged liver in patients undergoing MRE. STUDY TYPE Retrospective. SUBJECTS A total of 264 patients (n = 132 males, n = 132 females; mean age = 57 years) with suspected or known chronic liver disease underwent MRE paired with a liver protocol MRI. FIELD STRENGTH/SEQUENCE MRE was performed on a single 1.5 T scanner using a two-dimensional gradient-recalled echo phase-contrast sequence with a passive acoustic driver overlying the right hemiliver. ASSESSMENT Stiffness maps (usable data at 95% confidence) and liver contours on magnitude images of the MRE acquisition were manually traced and used to assess mean stiffness and pMLV. Hepatic fat fraction and R2 * values were also calculated. The distance from the acoustic wave generator on the skin surface to the liver edge was measured. Two radiologists performed the MR analyses with 50 overlapping cases for inter-reader analysis. STATISTICAL TESTS Linear regression was performed to identify factors significantly associated with pMLV. Intraclass correlation was performed for inter-reader reliability. RESULTS pMLV was 31% ± 20% (range 0%-86%). Complete MRE failure (i.e. pMLV = 0%) occurred in 10 patients (4%). Multivariate linear regression identified higher hepatic fat fraction, R2 *, BMI, and driver-to-liver surface distance; male sex; and lower mean liver stiffness was significantly independently associated with lower pMLV. Intraclass correlation for pMLV was 0.96, suggestive of excellent reliability. DATA CONCLUSION Higher fat fraction, R2 *, BMI, driver-to-liver surface distance, male sex, and lower mean liver stiffness were associated with lower pMLV. Optimization of image acquisition parameters and driver placement may improve MRE quality, and pMLV likely serves as a diagnostic utility quality control metric. LEVEL OF EVIDENCE 3 TECHNICAL EFFICACY STAGE: 2.
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Affiliation(s)
- David H Ballard
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Daniel R Ludwig
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Tyler J Fraum
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Amber Salter
- Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Vamsi R Narra
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Anup S Shetty
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
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Yoshizawa E, Yamada A. MRI-derived proton density fat fraction. J Med Ultrason (2001) 2021; 48:497-506. [PMID: 34669068 DOI: 10.1007/s10396-021-01135-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 07/26/2021] [Indexed: 11/26/2022]
Abstract
Reflecting the growing interest in early diagnosis of nonalcoholic fatty liver disease in recent years, the development of noninvasive and reliable fat quantification methods is required. Fat quantification by magnetic resonance imaging (MRI), especially MRI-derived proton density fat fraction (MRI-PDFF) obtained by quantitative chemical shift imaging such as the multi-point Dixon method, is highly correlated with histological evaluation and fat quantification with MR spectroscopy (MRS). In recent years, MRI-PDFF has been increasingly used as a reference standard for image-based fat quantification instead of MRS because it is possible to evaluate the whole liver with a single breath-hold. Furthermore, recent advances in MR imaging have led to the application of multiparametric MRI for the diagnosis of nonalcoholic fatty liver disease with specific liver tissue quantification of fat, iron, and fibrosis. One of the advantages of multiparametric MRI is that whole organ imaging to exclude sampling variability and organ-specific tissue quantification can be done simultaneously. Therefore, multiparametric MRI methods offer an attractive option for noninvasive and comprehensive liver assessment beyond the quantitative assessment of liver steatosis. In this review article, we mainly focus on a technical explanation and clinical interpretation of MRI-PDFF in the quantitative assessment of liver steatosis. Furthermore, we would like to mention future perspectives of MR imaging of the liver in relation to elastography and other specific multiparametric MRI methods such as R2* and T1 mapping.
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Affiliation(s)
- Eriko Yoshizawa
- Department of Radiology, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano, 390-2621, Japan
| | - Akira Yamada
- Department of Radiology, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano, 390-2621, Japan.
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Armstrong T, Zhong X, Shih SF, Felker E, Lu DS, Dale BM, Wu HH. Free-breathing 3D stack-of-radial MRI quantification of liver fat and R 2* in adults with fatty liver disease. Magn Reson Imaging 2021; 85:141-152. [PMID: 34662702 DOI: 10.1016/j.mri.2021.10.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 10/07/2021] [Accepted: 10/12/2021] [Indexed: 02/07/2023]
Abstract
PURPOSE To investigate the agreement, intra-session repeatability, and inter-reader agreement of liver proton-density fat fraction (PDFF) and R2* quantification using free-breathing 3D stack-of-radial MRI, with and without self-gated motion compensation, compared to reference breath-hold techniques in subjects with fatty liver disease (FLD). METHODS In this institutional review board-approved prospective study, thirty-eight adults with FLD and/or iron overload (24 male, 58 ± 12 years) were imaged at 3T using free-breathing stack-of-radial MRI, breath-hold 3D Cartesian MRI, and breath-hold single-voxel MR spectroscopy (SVS). Each sequence was acquired twice in random order. To assess agreement compared to reference breath-hold techniques, the dependency of liver PDFF and/or R2* quantification on the sequence, radial sampling factor, and radial self-gating temporal resolution was assessed by calculating the Bayesian mean difference (MDB) of the posteriors. Intra-session repeatability and inter-reader agreement (two independent readers) were assessed by the coefficient of repeatability (CR) and intraclass correlation coefficient (ICC), respectively. RESULTS Thirty-five participants (21 male, 57 ± 12 years) were included for analysis. Both free-breathing radial MRI techniques (with and without self-gating) achieved ICC ≥ 0.92 for quantifying PDFF and R2*, and quantified PDFF with MDB < 1.2% compared to breath-hold techniques. Free-breathing radial MRI required self-gating to accurately quantify R2* (MDB < 10s-1 with self-gating; MDB < 50s-1 without self-gating). The radial sampling factor affected PDFF and R2* quantification while the radial self-gating temporal resolution only affected R2* quantification. Repeated self-gated free-breathing radial MRI scans achieved CR < 3% and CR < 27 s-1 for PDFF and R2*, respectively. CONCLUSION A free-breathing stack-of-radial MRI technique with self-gating demonstrated agreement, repeatability, and inter-reader agreement compared to reference breath-hold techniques for quantification of liver PDFF and R2* in adults with FLD.
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Affiliation(s)
- Tess Armstrong
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States
| | - Xiaodong Zhong
- MR R&D Collaborations, Siemens Medical Solutions USA, Inc., Los Angeles, CA, United States
| | - Shu-Fu Shih
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States; Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, United States
| | - Ely Felker
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States
| | - David S Lu
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States
| | - Brian M Dale
- MR R&D Collaborations, Siemens Medical Solutions USA, Inc., Cary, NC, United States
| | - Holden H Wu
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States; Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, United States.
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Colgan TJ, Zhao R, Roberts NT, Hernando D, Reeder SB. Limits of Fat Quantification in the Presence of Iron Overload. J Magn Reson Imaging 2021; 54:1166-1174. [PMID: 33783066 PMCID: PMC8440489 DOI: 10.1002/jmri.27611] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 03/09/2021] [Accepted: 03/10/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Chemical shift encoded magnetic resonance imaging (CSE-MRI)-based tissue fat quantification is confounded by increased R2* signal decay rate caused by the presence of excess iron deposition. PURPOSE To determine the upper limit of R2* above which it is no longer feasible to quantify proton density fat fraction (PDFF) reliably, using CSE-MRI. STUDY TYPE Prospective. POPULATION Cramér-Rao lower bound (CRLB) calculations, Monte Carlo simulations, phantom experiments, and a prospective study in 26 patients with known or suspected liver iron overload. FIELD STRENGTH/SEQUENCE Multiecho gradient echo at 1.5 T and 3.0 T. ASSESSMENT CRLB calculations were used to develop an empirical relationship between the maximum R2* value above which PDFF estimation will achieve a desired number of effective signal averages. A single voxel multi-TR, multi-TE stimulated echo acquisition mode magnetic resonance spectroscopy acquisition was used as a reference standard to estimate PDFF. Reconstructed PDFF and R2* maps were analyzed by one analyst using multiple regions of interest drawn in all nine Couinaud segments. STATISTICAL TESTS None. RESULTS Simulations, phantom experiments, and in vivo measurements demonstrated unreliable PDFF estimates with increased R2*, with PDFF errors as large as 20% at an R2* of 1000 s-1 . For typical optimized Cartesian acquisitions (TE1 = 0.75 msec, ΔTE = 0.67 msec at 1.5 T, TE1 = 0.65 msec, ΔTE = 0.58 msec at 3.0 T), an empirical relationship between PDFF estimation errors and acquisition parameters was developed that suggests PDFF estimates are unreliable above an R2* of ~538 s-1 and ~779 s-1 at 1.5 T and 3 T, respectively. This empirical relationship was further investigated with phantom experiments and in vivo measurements, with PDFF errors at an R2* of 1000 s-1 at 3.0 T as large as 10% with TE1 = 1.24 msec, ΔTE = 1.01 msec compared to 3% with TE1 = 0.65 msec, ΔTE = 0.58 msec. DATA CONCLUSION We successfully developed a theoretically-based empirical formula that may provide an easily calculable guideline to identify R2* values above which PDFF is not reliable in research and clinical applications using CSE-MRI to quantify PDFF in the presence of iron overload. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY STAGE: 1.
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Affiliation(s)
- Timothy J Colgan
- Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA
| | - Ruiyang Zhao
- Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA
- Department of Electrical and Computer Engineering, University of Wisconsin, Madison, Wisconsin, USA
| | - Nathan T Roberts
- Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA
- Department of Electrical and Computer Engineering, University of Wisconsin, Madison, Wisconsin, USA
| | - Diego Hernando
- Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin, Madison, Wisconsin, USA
| | - Scott B Reeder
- Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin, Madison, Wisconsin, USA
- Department of Biomedical Engineering, University of Wisconsin, Madison, Wisconsin, USA
- Department of Medicine, University of Wisconsin, Madison, Wisconsin, USA
- Department of Emergency Medicine, University of Wisconsin, Madison, Wisconsin, USA
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Simchick G, Zhao R, Hamilton G, Reeder SB, Hernando D. Spectroscopy-based multi-parametric quantification in subjects with liver iron overload at 1.5T and 3T. Magn Reson Med 2021; 87:597-613. [PMID: 34554595 DOI: 10.1002/mrm.29021] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 08/13/2021] [Accepted: 09/07/2021] [Indexed: 01/02/2023]
Abstract
PURPOSE To evaluate the precision profile (repeatability and reproducibility) of quantitative STEAM-MRS and to determine the relationships between multiple MR biomarkers of chronic liver disease in subjects with iron overload at both 1.5 Tesla (T) and 3T. METHODS MRS data were acquired in patients with known or suspected liver iron overload. Two STEAM-MRS sequences (multi-TE and multi-TE-TR) were acquired at both 1.5T and 3T (same day), including test-retest acquisition. Each acquisition enabled estimation of R1, R2, and FWHM (each separately for water and fat); and proton density fat fraction. The test-retest repeatability and reproducibility across acquisition modes (multi-TE vs. multi-TE-TR) of the estimates were evaluated using intraclass correlation coefficients, linear regression, and Bland-Altman analyses. Multi-parametric relationships between parameters at each field strength, across field strengths, and with liver iron concentration were also evaluated using linear and nonlinear regression. RESULTS Fifty-six (n = 56) subjects (10 to 73 years, 37 males/19 females) were successfully recruited. Both STEAM-MRS sequences demonstrated good-to-excellent precision (intraclass correlation coefficient ≥ 0.81) for the quantification of R1water , R2water , FWHMwater , and proton density fat fraction at both 1.5T and 3T. Additionally, several moderate (R2 = 0.50 to 0.69) to high (R2 ≥ 0.70) correlations were observed between biomarkers, across field strengths, and with liver iron concentration. CONCLUSIONS Over a broad range of liver iron concentration, STEAM-MRS enables rapid and precise measurement of multiple biomarkers of chronic liver disease. By evaluating the multi-parametric relationships between biomarkers, this work may advance the comprehensive MRS-based assessment of chronic liver disease and may help establish biomarkers of chronic liver disease.
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Affiliation(s)
- Gregory Simchick
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Ruiyang Zhao
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Gavin Hamilton
- Department of Radiology, University of California, San Diego, California, USA
| | - Scott B Reeder
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Medicine, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Emergency Medicine, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Diego Hernando
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA
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Shao CX, Ye J, Dong Z, Li F, Lin Y, Liao B, Feng S, Zhong B. Steatosis grading consistency between controlled attenuation parameter and MRI-PDFF in monitoring metabolic associated fatty liver disease. Ther Adv Chronic Dis 2021; 12:20406223211033119. [PMID: 34408822 PMCID: PMC8366131 DOI: 10.1177/20406223211033119] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Accepted: 06/21/2021] [Indexed: 12/29/2022] Open
Abstract
Background The consistency in steatosis grading between magnetic resonance imaging-based proton density fat fraction (MRI-PDFF) and controlled attenuation parameter (CAP) before and after treatment remains unclear. This study aimed to compare the diagnostic accuracy of steatosis grading between MRI-PDFF and CAP using liver biopsy as standard and to evaluate the value of monitoring changes in steatosis grading with CAP during follow-up utilizing MRI-PDFF as a reference. Methods Consecutive patients from a biopsy cohort and a randomized controlled trial were included in this study and classified into 3 groups (the biopsy, orlistat treatment, and routine treatment subgroups). Hepatic steatosis was measured via MRI-PDFF and CAP at baseline and at the 6th month; the accuracy and cutoffs were assessed in the liver biopsy cohort at baseline. Results A total of 209 consecutive patients were enrolled. MRI-PDFF and CAP showed comparable diagnostic accuracy for detecting pathological steatosis [⩾S1, area under the receiver operating characteristic curve (AUC) = 0.984 and 0.972, respectively]; in contrast, CAP presented significantly lower AUCs in grades S2-3 and S3 (0.820 and 0.815, respectively). The CAP values correlated well with the MRI-PDFF values at baseline and at the 6th month (r = 0.809 and 0.762, respectively, both p < 0.001), whereas a moderate correlation in their changes (r = 0.612 and 0.524 for moderate-severe and mild steatosis, respectively; both p < 0.001) was observed. The AUC of CAP change was obtained to predict MRI-PDFF changes of ⩾5% and ⩾10% (0.685 and 0.704, p < 0.001 and p = 0.001, respectively). The diagnostic agreement of steatosis grade changes between MRI-PDFF and CAP was weak (κ = 0.181, p = 0.001). Conclusions CAP has decreased value for the initial screening of moderate-severe steatosis and is limited in monitoring changes in steatosis during treatment. The confirmation of steatosis grading with MRI-PDFF remains necessary.
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Affiliation(s)
- Cong Xiang Shao
- Department of Gastroenterology of the First Affiliated Hospital, Sun Yat-sen University, Yuexiu District, Guangzhou, China
| | - Junzhao Ye
- Department of Gastroenterology of the First Affiliated Hospital, Sun Yat-sen University, Yuexiu District, Guangzhou, China
| | - Zhi Dong
- Department of Radiology of the First Affiliated Hospital, Sun Yat-sen University, Yuexiu District, Guangzhou, China
| | - Fuxi Li
- Department of Gastroenterology of the First Affiliated Hospital, Sun Yat-sen University, Yuexiu District, Guangzhou, China
| | - Yansong Lin
- Department of Gastroenterology of the First Affiliated Hospital, Sun Yat-sen University, Yuexiu District, Guangzhou, China
| | - Bing Liao
- Department of Pathology of the First Affiliated Hospital, Sun Yat-sen University, Yuexiu District, Guangzhou, China
| | - Shiting Feng
- Department of Radiology of the First Affiliated Hospital, Sun Yat-sen University, Yuexiu District, Guangzhou, China
| | - Bihui Zhong
- Department of Gastroenterology of the First Affiliated Hospital, Sun Yat-sen University, No. 58 Zhongshan II Road, Yuexiu District, Guangzhou, 510080, China
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Influence of arm position on proton density fat fraction in the liver using chemical shift-encoded magnetic resonance imaging. Magn Reson Imaging 2021; 83:133-138. [PMID: 34365005 DOI: 10.1016/j.mri.2021.08.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 07/05/2021] [Accepted: 08/03/2021] [Indexed: 11/20/2022]
Abstract
PURPOSE To evaluate the influence of arm position on B1 and proton density fat fraction (PDFF) in the liver using chemical shift-encoded magnetic resonance imaging. MATERIALS AND METHODS Participants were 8 healthy volunteers without liver disease and 36 patients with presumed or proven fatty liver. We assessed two preliminary examinations in healthy subjects, i.e., arm position influence on B1 and the variability of the PDFF between two scans within a short period of time. To verify the changes in PDFF measurement, 36 patients with fatty liver were conducted to compare 2 different arm positions-the elevated arms and side arms positions. The measurement location was based on the Healey & Schroy classification. The Wilcoxon test was used to analyze the difference in B1 in between the elevated arms and side arms positions. The Bland-Altman analysis was used to assess the agreement between two measurements of PDFF: two same scans within a short period of time, and two scans with different arms positions. RESULTS B1 was significantly different in all segments except for medial segment. The variability of the PDFF between two scans within a short period of time was small in all segments. Some patients had large fluctuations in all segments, although the mean differences in PDFF were small. Upper and lower limits of agreement were 2.064% to 2.871% and - 2.430% to -1.462%, respectively. The relative difference in the rate of PDFF changes as the median (interquartile range [IQR]) in the lateral, medial, anterior, and posterior segments between both the arms positions were 0.0% (9.4), 1.1% (7.3), 1.5% (8.2) and - 0.2% (10.3), respectively. CONCLUSIONS Arm position can significantly affect B1 and PDFF in the liver. Although the absolute change in PDFF between arm positions was not so large, the difference in arm positions can cause large relative PDFF fluctuations.
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Kumar D, Link TM, Jafarzadeh SR, LaValley MP, Majumdar S, Souza RB. Association of Quadriceps Adiposity With an Increase in Knee Cartilage, Meniscus, or Bone Marrow Lesions Over Three Years. Arthritis Care Res (Hoboken) 2021; 73:1134-1139. [PMID: 32339414 PMCID: PMC7606313 DOI: 10.1002/acr.24232] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Accepted: 04/21/2020] [Indexed: 12/25/2022]
Abstract
OBJECTIVE To evaluate the association of fatty infiltration of the quadriceps and vastus medialis (VM) with an increase in knee cartilage, meniscus, or bone marrow lesions, using magnetic resonance imaging (MRI) in knee osteoarthritis (OA) over 3 years. METHODS Participants (n = 69) with and without radiographic knee OA underwent MRI at baseline and 3 years later. Chemical shift-based water/fat MRI was used to quantify the intramuscular fat fraction and the lean anatomical cross-sectional area (ACSA) for the VM and entire quadriceps muscles. MRI images of the knee were analyzed using the semiquantitative modified whole-organ MRI score (mWORMS) grading to assess change in lesions in the articular cartilage, meniscus, and bone marrow. Logistic regression was used to assess whether baseline quadriceps and VM fat fraction and lean ACSA were associated with an increase in mWORMS scores. Odds ratios (ORs) were adjusted for age, sex, and body mass index. RESULTS Overall, of the 69 subjects, 43 (62%) had an increase in cartilage lesions (26 of 43), meniscus lesions (19 of 43), or bone marrow lesions (22 of 43) scores. The quadriceps (OR 2.13 [95% confidence interval (95% CI) 1.09-4.15]) and VM (OR 2.05 [95% CI 1.25-3.36]) fat fraction were both associated with an increase in cartilage, meniscus, or bone marrow lesion scores over 3 years. The association of quadriceps or VM lean ACSA with the outcomes was not significant. CONCLUSION These longitudinal findings using quantitative MRI methods for assessment of muscle adiposity highlight the role of quadriceps adiposity, specifically in the VM, in knee OA progression. However, studies in larger cohorts are needed to confirm these findings.
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Affiliation(s)
- Deepak Kumar
- Department of Physical Therapy & Athletic Training, College of Health and Rehabilitation Sciences: Sargent College, Boston University, Boston, MA, USA,Section of Rheumatology, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Thomas M. Link
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - S. Reza Jafarzadeh
- Section of Rheumatology, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Michael P. LaValley
- Section of Rheumatology, Department of Medicine, Boston University School of Medicine, Boston, MA, USA,Department of Biostatistics, School of Public Health, Boston University
| | - Sharmila Majumdar
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Richard B. Souza
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA,Department of Physical Therapy and Rehabilitation Science, University of California, San Francisco, CA, USA
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Shrestha U, van der Merwe M, Kumar N, Jacobs E, Satapathy SK, Morin C, Tipirneni-Sajja A. Morphological characterization of hepatic steatosis and Monte Carlo modeling of MRI signal for accurate quantification of fat fraction and relaxivity. NMR IN BIOMEDICINE 2021; 34:e4489. [PMID: 33586261 DOI: 10.1002/nbm.4489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2020] [Revised: 12/16/2020] [Accepted: 01/25/2021] [Indexed: 06/12/2023]
Abstract
Chemical-shift-based fat-water MRI signal models with single- or dual-R2 * correction have been proposed for quantification of fat fraction (FF) and assessment of hepatic steatosis. However, there is a void in our understanding of which model truly mimics the underlying biophysical mechanism of steatosis on MRI signal relaxation. The purpose of this study is to morphologically characterize and build realistic steatosis models from histology and synthesize MRI signal using Monte Carlo simulations to investigate the accuracy of single- and dual-R2 * models in quantifying FF and R2 *. Fat morphology was characterized by performing automatic segmentation on 16 mouse liver histology images and extracting the radius, nearest neighbor (NN) distance, and regional anisotropy of fat droplets. A gamma distribution function (GDF) was used to generalize extracted features, and regression analysis was performed to derive relationships between FF and GDF parameters. Virtual steatosis models were created based on derived morphological and statistical descriptors, and the MRI signal was synthesized at 1.5 T and 3 T. R2 * and FF values were calculated using single- and dual-R2 * models and compared with in vivo R2 *-FF calibrations and simulated FFs. The steatosis models generated with regional anisotropy and NN distribution closely mimicked the true in vivo fat morphology. For both R2 * models, predicted R2 * values showed positive correlation with FFs, with slopes similar to those of the in vivo calibrations (P > 0.05), and predicted FFs showed excellent agreement with true FFs (R2 > 0.99), with slopes close to unity. Our study, hence, demonstrates the proof of concept for generating steatosis models from histologic data and synthesizing MRI signal to show the expected signal relaxation under conditions of steatosis. Our results suggest that a single R2 * is sufficient to accurately estimate R2 * and FF values for lower FFs, which agrees with in vivo studies. Future work involves characterizing and building steatosis models at higher FFs and testing single- and dual-R2 * models for accurate assessment of steatosis.
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Affiliation(s)
- Utsav Shrestha
- Department of Biomedical Engineering, The University of Memphis, Memphis, Tennessee, USA
- Department of Computer Science, The University of Memphis, Memphis, Tennessee, USA
| | - Marie van der Merwe
- College of Health Sciences, The University of Memphis, Memphis, Tennessee, USA
| | - Nirman Kumar
- Department of Computer Science, The University of Memphis, Memphis, Tennessee, USA
| | - Eddie Jacobs
- Department of Electrical & Computer Engineering, The University of Memphis, Memphis, Tennessee, USA
| | - Sanjaya K Satapathy
- Department of Medicine, North Shore University Hospital/Northwell Health, Manhasset, New York, USA
| | - Cara Morin
- Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Aaryani Tipirneni-Sajja
- Department of Biomedical Engineering, The University of Memphis, Memphis, Tennessee, USA
- Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
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Beyer C, Hutton C, Andersson A, Imajo K, Nakajima A, Kiker D, Banerjee R, Dennis A. Comparison between magnetic resonance and ultrasound-derived indicators of hepatic steatosis in a pooled NAFLD cohort. PLoS One 2021; 16:e0249491. [PMID: 33793651 PMCID: PMC8016312 DOI: 10.1371/journal.pone.0249491] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Accepted: 03/17/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND & AIMS MRI-based proton density fat fraction (PDFF) and the ultrasound-derived controlled attenuation parameter (CAP) are non-invasive techniques for quantifying liver fat, which can be used to assess steatosis in patients with non-alcoholic fatty liver disease (NAFLD). This study compared both of these techniques to histopathological graded steatosis for the assessment of fat levels in a large pooled NAFLD cohort. METHODS This retrospective study pooled N = 581 participants from two suspected NAFLD cohorts (mean age (SD) 56 (12.7), 60% females). Steatosis was graded according to NASH-CRN criteria. Liver fat was measured non-invasively using PDFF (with Liver MultiScan's Iterative Decomposition of water and fat with Echo Asymmetry and Least-squares estimation method, LMS-IDEAL, Perspectum, Oxford) and CAP (FibroScan, Echosens, France), and their diagnostic performances were compared. RESULTS LMS-IDEAL and CAP detected steatosis grade ≥ 1 with AUROCs of 1.00 (95% CI, 0.99-1.0) and 0.95 (95% CI, 0.91-0.99), respectively. LMS-IDEAL was superior to CAP for detecting steatosis grade ≥ 2 with AUROCs of 0.77 (95% CI, 0.73-0.82] and 0.60 (95% CI, 0.55-0.65), respectively. Similarly, LMS-IDEAL outperformed CAP for detecting steatosis grade ≥ 3 with AUROCs of 0.81 (95% CI, 0.76-0.87) and 0.63 (95% CI, 0.56-0.70), respectively. CONCLUSION LMS-IDEAL was able to diagnose individuals accurately across the spectrum of histological steatosis grades. CAP performed well in identifying individuals with lower levels of fat (steatosis grade ≥1); however, its diagnostic performance was inferior to LMS-IDEAL for higher levels of fat (steatosis grades ≥2 and ≥3). TRIAL REGISTRATION ClinicalTrials.gov (NCT03551522); https://clinicaltrials.gov/ct2/show/NCT03551522. UMIN Clinical Trials Registry (UMIN000026145); https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000026145.
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Affiliation(s)
| | | | | | - Kento Imajo
- Department of Gastroenterology and Hepatology, Yokohama City University Graduate School of Medicine, Yokohama, Japan
| | - Atsushi Nakajima
- Department of Gastroenterology and Hepatology, Yokohama City University Graduate School of Medicine, Yokohama, Japan
| | - Dustin Kiker
- Texas Digestive Disease Consultants, Dallas, Texas, United States of America
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Jeon KJ, Lee C, Choi YJ, Han SS. Assessment of bone marrow fat fractions in the mandibular condyle head using the iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL-IQ) method. PLoS One 2021; 16:e0246596. [PMID: 33635882 PMCID: PMC7909693 DOI: 10.1371/journal.pone.0246596] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Accepted: 01/22/2021] [Indexed: 12/25/2022] Open
Abstract
The prevalence of temporomandibular joint disorder (TMD) is gradually increasing, and magnetic resonance imaging (MRI) is becoming increasingly common as a modality used to diagnose TMD. Edema and osteonecrosis in the bone marrow of the mandibular condyle have been considered to be precursors of osteoarthritis, but these changes are not evaluated accurately and quantitatively on routine MRI. The iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL-IQ) method, as a cutting-edge MRI technique, can separate fat and water using three asymmetric echo times and the three-point Dixon method. The purpose of this study was to analyze the quantitative fat fraction (FF) in the mandibular condyle head using the IDEAL-IQ method. Seventy-nine people who underwent MRI using IDEAL-IQ were investigated and divided into 1) the control group, without TMD symptoms, and 2) the TMD group, with unilateral temporomandibular joint (TMJ) pain. In both groups, the FF of the condyle head in the TMJ was analyzed by two oral and maxillofacial radiologists. In the TMD group, 29 people underwent cone-beam computed tomography (CBCT) and the presence or absence of bony changes in the condylar head was evaluated. The FF measurements of the condyle head using IDEAL-IQ showed excellent inter-observer and intra-observer agreement. The average FF of the TMD group was significantly lower than that of the control group (p < 0.05). In the TMD group, the average FF values of joints with pain and joints with bony changes were significantly lower than those of joints without pain or bony changes, respectively (p < 0.05). The FF using IDEAL-IQ in the TMJ can be helpful for the quantitative diagnosis of TMD.
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Affiliation(s)
- Kug Jin Jeon
- Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, Seoul, Republic of Korea
| | - Chena Lee
- Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, Seoul, Republic of Korea
| | - Yoon Joo Choi
- Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, Seoul, Republic of Korea
| | - Sang-Sun Han
- Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, Seoul, Republic of Korea
- * E-mail:
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